keyword stringclasses 7 values | repo_name stringlengths 8 98 | file_path stringlengths 4 244 | file_extension stringclasses 29 values | file_size int64 0 84.1M | line_count int64 0 1.6M | content stringlengths 1 84.1M ⌀ | language stringclasses 14 values |
|---|---|---|---|---|---|---|---|
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/lapack/clarf.f | .f | 6,295 | 233 | *> \brief \b CLARF
*
* =========== DOCUMENTATION ===========
*
* Online html documentation available at
* http://www.netlib.org/lapack/explore-html/
*
*> \htmlonly
*> Download CLARF + dependencies
*> <a href="http://www.netlib.org/cgi-bin/netlibfiles.tgz?format=tgz&filename=/lapack/lapack_routine/clarf.f">
*> [TGZ]</a>
*> <a href="http://www.netlib.org/cgi-bin/netlibfiles.zip?format=zip&filename=/lapack/lapack_routine/clarf.f">
*> [ZIP]</a>
*> <a href="http://www.netlib.org/cgi-bin/netlibfiles.txt?format=txt&filename=/lapack/lapack_routine/clarf.f">
*> [TXT]</a>
*> \endhtmlonly
*
* Definition:
* ===========
*
* SUBROUTINE CLARF( SIDE, M, N, V, INCV, TAU, C, LDC, WORK )
*
* .. Scalar Arguments ..
* CHARACTER SIDE
* INTEGER INCV, LDC, M, N
* COMPLEX TAU
* ..
* .. Array Arguments ..
* COMPLEX C( LDC, * ), V( * ), WORK( * )
* ..
*
*
*> \par Purpose:
* =============
*>
*> \verbatim
*>
*> CLARF applies a complex elementary reflector H to a complex M-by-N
*> matrix C, from either the left or the right. H is represented in the
*> form
*>
*> H = I - tau * v * v**H
*>
*> where tau is a complex scalar and v is a complex vector.
*>
*> If tau = 0, then H is taken to be the unit matrix.
*>
*> To apply H**H (the conjugate transpose of H), supply conjg(tau) instead
*> tau.
*> \endverbatim
*
* Arguments:
* ==========
*
*> \param[in] SIDE
*> \verbatim
*> SIDE is CHARACTER*1
*> = 'L': form H * C
*> = 'R': form C * H
*> \endverbatim
*>
*> \param[in] M
*> \verbatim
*> M is INTEGER
*> The number of rows of the matrix C.
*> \endverbatim
*>
*> \param[in] N
*> \verbatim
*> N is INTEGER
*> The number of columns of the matrix C.
*> \endverbatim
*>
*> \param[in] V
*> \verbatim
*> V is COMPLEX array, dimension
*> (1 + (M-1)*abs(INCV)) if SIDE = 'L'
*> or (1 + (N-1)*abs(INCV)) if SIDE = 'R'
*> The vector v in the representation of H. V is not used if
*> TAU = 0.
*> \endverbatim
*>
*> \param[in] INCV
*> \verbatim
*> INCV is INTEGER
*> The increment between elements of v. INCV <> 0.
*> \endverbatim
*>
*> \param[in] TAU
*> \verbatim
*> TAU is COMPLEX
*> The value tau in the representation of H.
*> \endverbatim
*>
*> \param[in,out] C
*> \verbatim
*> C is COMPLEX array, dimension (LDC,N)
*> On entry, the M-by-N matrix C.
*> On exit, C is overwritten by the matrix H * C if SIDE = 'L',
*> or C * H if SIDE = 'R'.
*> \endverbatim
*>
*> \param[in] LDC
*> \verbatim
*> LDC is INTEGER
*> The leading dimension of the array C. LDC >= max(1,M).
*> \endverbatim
*>
*> \param[out] WORK
*> \verbatim
*> WORK is COMPLEX array, dimension
*> (N) if SIDE = 'L'
*> or (M) if SIDE = 'R'
*> \endverbatim
*
* Authors:
* ========
*
*> \author Univ. of Tennessee
*> \author Univ. of California Berkeley
*> \author Univ. of Colorado Denver
*> \author NAG Ltd.
*
*> \date November 2011
*
*> \ingroup complexOTHERauxiliary
*
* =====================================================================
SUBROUTINE CLARF( SIDE, M, N, V, INCV, TAU, C, LDC, WORK )
*
* -- LAPACK auxiliary routine (version 3.4.0) --
* -- LAPACK is a software package provided by Univ. of Tennessee, --
* -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
* November 2011
*
* .. Scalar Arguments ..
CHARACTER SIDE
INTEGER INCV, LDC, M, N
COMPLEX TAU
* ..
* .. Array Arguments ..
COMPLEX C( LDC, * ), V( * ), WORK( * )
* ..
*
* =====================================================================
*
* .. Parameters ..
COMPLEX ONE, ZERO
PARAMETER ( ONE = ( 1.0E+0, 0.0E+0 ),
$ ZERO = ( 0.0E+0, 0.0E+0 ) )
* ..
* .. Local Scalars ..
LOGICAL APPLYLEFT
INTEGER I, LASTV, LASTC
* ..
* .. External Subroutines ..
EXTERNAL CGEMV, CGERC
* ..
* .. External Functions ..
LOGICAL LSAME
INTEGER ILACLR, ILACLC
EXTERNAL LSAME, ILACLR, ILACLC
* ..
* .. Executable Statements ..
*
APPLYLEFT = LSAME( SIDE, 'L' )
LASTV = 0
LASTC = 0
IF( TAU.NE.ZERO ) THEN
! Set up variables for scanning V. LASTV begins pointing to the end
! of V.
IF( APPLYLEFT ) THEN
LASTV = M
ELSE
LASTV = N
END IF
IF( INCV.GT.0 ) THEN
I = 1 + (LASTV-1) * INCV
ELSE
I = 1
END IF
! Look for the last non-zero row in V.
DO WHILE( LASTV.GT.0 .AND. V( I ).EQ.ZERO )
LASTV = LASTV - 1
I = I - INCV
END DO
IF( APPLYLEFT ) THEN
! Scan for the last non-zero column in C(1:lastv,:).
LASTC = ILACLC(LASTV, N, C, LDC)
ELSE
! Scan for the last non-zero row in C(:,1:lastv).
LASTC = ILACLR(M, LASTV, C, LDC)
END IF
END IF
! Note that lastc.eq.0 renders the BLAS operations null; no special
! case is needed at this level.
IF( APPLYLEFT ) THEN
*
* Form H * C
*
IF( LASTV.GT.0 ) THEN
*
* w(1:lastc,1) := C(1:lastv,1:lastc)**H * v(1:lastv,1)
*
CALL CGEMV( 'Conjugate transpose', LASTV, LASTC, ONE,
$ C, LDC, V, INCV, ZERO, WORK, 1 )
*
* C(1:lastv,1:lastc) := C(...) - v(1:lastv,1) * w(1:lastc,1)**H
*
CALL CGERC( LASTV, LASTC, -TAU, V, INCV, WORK, 1, C, LDC )
END IF
ELSE
*
* Form C * H
*
IF( LASTV.GT.0 ) THEN
*
* w(1:lastc,1) := C(1:lastc,1:lastv) * v(1:lastv,1)
*
CALL CGEMV( 'No transpose', LASTC, LASTV, ONE, C, LDC,
$ V, INCV, ZERO, WORK, 1 )
*
* C(1:lastc,1:lastv) := C(...) - w(1:lastc,1) * v(1:lastv,1)**H
*
CALL CGERC( LASTC, LASTV, -TAU, WORK, 1, V, INCV, C, LDC )
END IF
END IF
RETURN
*
* End of CLARF
*
END
| Fortran |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/lapack/dladiv.f | .f | 2,969 | 129 | *> \brief \b DLADIV
*
* =========== DOCUMENTATION ===========
*
* Online html documentation available at
* http://www.netlib.org/lapack/explore-html/
*
*> \htmlonly
*> Download DLADIV + dependencies
*> <a href="http://www.netlib.org/cgi-bin/netlibfiles.tgz?format=tgz&filename=/lapack/lapack_routine/dladiv.f">
*> [TGZ]</a>
*> <a href="http://www.netlib.org/cgi-bin/netlibfiles.zip?format=zip&filename=/lapack/lapack_routine/dladiv.f">
*> [ZIP]</a>
*> <a href="http://www.netlib.org/cgi-bin/netlibfiles.txt?format=txt&filename=/lapack/lapack_routine/dladiv.f">
*> [TXT]</a>
*> \endhtmlonly
*
* Definition:
* ===========
*
* SUBROUTINE DLADIV( A, B, C, D, P, Q )
*
* .. Scalar Arguments ..
* DOUBLE PRECISION A, B, C, D, P, Q
* ..
*
*
*> \par Purpose:
* =============
*>
*> \verbatim
*>
*> DLADIV performs complex division in real arithmetic
*>
*> a + i*b
*> p + i*q = ---------
*> c + i*d
*>
*> The algorithm is due to Robert L. Smith and can be found
*> in D. Knuth, The art of Computer Programming, Vol.2, p.195
*> \endverbatim
*
* Arguments:
* ==========
*
*> \param[in] A
*> \verbatim
*> A is DOUBLE PRECISION
*> \endverbatim
*>
*> \param[in] B
*> \verbatim
*> B is DOUBLE PRECISION
*> \endverbatim
*>
*> \param[in] C
*> \verbatim
*> C is DOUBLE PRECISION
*> \endverbatim
*>
*> \param[in] D
*> \verbatim
*> D is DOUBLE PRECISION
*> The scalars a, b, c, and d in the above expression.
*> \endverbatim
*>
*> \param[out] P
*> \verbatim
*> P is DOUBLE PRECISION
*> \endverbatim
*>
*> \param[out] Q
*> \verbatim
*> Q is DOUBLE PRECISION
*> The scalars p and q in the above expression.
*> \endverbatim
*
* Authors:
* ========
*
*> \author Univ. of Tennessee
*> \author Univ. of California Berkeley
*> \author Univ. of Colorado Denver
*> \author NAG Ltd.
*
*> \date November 2011
*
*> \ingroup auxOTHERauxiliary
*
* =====================================================================
SUBROUTINE DLADIV( A, B, C, D, P, Q )
*
* -- LAPACK auxiliary routine (version 3.4.0) --
* -- LAPACK is a software package provided by Univ. of Tennessee, --
* -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
* November 2011
*
* .. Scalar Arguments ..
DOUBLE PRECISION A, B, C, D, P, Q
* ..
*
* =====================================================================
*
* .. Local Scalars ..
DOUBLE PRECISION E, F
* ..
* .. Intrinsic Functions ..
INTRINSIC ABS
* ..
* .. Executable Statements ..
*
IF( ABS( D ).LT.ABS( C ) ) THEN
E = D / C
F = C + D*E
P = ( A+B*E ) / F
Q = ( B-A*E ) / F
ELSE
E = C / D
F = D + C*E
P = ( B+A*E ) / F
Q = ( -A+B*E ) / F
END IF
*
RETURN
*
* End of DLADIV
*
END
| Fortran |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/scripts/eigen_gen_credits.cpp | .cpp | 6,384 | 233 | #include <string>
#include <sstream>
#include <iostream>
#include <fstream>
#include <iomanip>
#include <map>
#include <list>
using namespace std;
// this function takes a line that may contain a name and/or email address,
// and returns just the name, while fixing the "bad cases".
std::string contributor_name(const std::string& line)
{
string result;
// let's first take care of the case of isolated email addresses, like
// "user@localhost.localdomain" entries
if(line.find("markb@localhost.localdomain") != string::npos)
{
return "Mark Borgerding";
}
if(line.find("kayhman@contact.intra.cea.fr") != string::npos)
{
return "Guillaume Saupin";
}
// from there on we assume that we have a entry of the form
// either:
// Bla bli Blurp
// or:
// Bla bli Blurp <bblurp@email.com>
size_t position_of_email_address = line.find_first_of('<');
if(position_of_email_address != string::npos)
{
// there is an e-mail address in <...>.
// Hauke once committed as "John Smith", fix that.
if(line.find("hauke.heibel") != string::npos)
result = "Hauke Heibel";
else
{
// just remove the e-mail address
result = line.substr(0, position_of_email_address);
}
}
else
{
// there is no e-mail address in <...>.
if(line.find("convert-repo") != string::npos)
result = "";
else
result = line;
}
// remove trailing spaces
size_t length = result.length();
while(length >= 1 && result[length-1] == ' ') result.erase(--length);
return result;
}
// parses hg churn output to generate a contributors map.
map<string,int> contributors_map_from_churn_output(const char *filename)
{
map<string,int> contributors_map;
string line;
ifstream churn_out;
churn_out.open(filename, ios::in);
while(!getline(churn_out,line).eof())
{
// remove the histograms "******" that hg churn may draw at the end of some lines
size_t first_star = line.find_first_of('*');
if(first_star != string::npos) line.erase(first_star);
// remove trailing spaces
size_t length = line.length();
while(length >= 1 && line[length-1] == ' ') line.erase(--length);
// now the last space indicates where the number starts
size_t last_space = line.find_last_of(' ');
// get the number (of changesets or of modified lines for each contributor)
int number;
istringstream(line.substr(last_space+1)) >> number;
// get the name of the contributor
line.erase(last_space);
string name = contributor_name(line);
map<string,int>::iterator it = contributors_map.find(name);
// if new contributor, insert
if(it == contributors_map.end())
contributors_map.insert(pair<string,int>(name, number));
// if duplicate, just add the number
else
it->second += number;
}
churn_out.close();
return contributors_map;
}
// find the last name, i.e. the last word.
// for "van den Schbling" types of last names, that's not a problem, that's actually what we want.
string lastname(const string& name)
{
size_t last_space = name.find_last_of(' ');
if(last_space >= name.length()-1) return name;
else return name.substr(last_space+1);
}
struct contributor
{
string name;
int changedlines;
int changesets;
string url;
string misc;
contributor() : changedlines(0), changesets(0) {}
bool operator < (const contributor& other)
{
return lastname(name).compare(lastname(other.name)) < 0;
}
};
void add_online_info_into_contributors_list(list<contributor>& contributors_list, const char *filename)
{
string line;
ifstream online_info;
online_info.open(filename, ios::in);
while(!getline(online_info,line).eof())
{
string hgname, realname, url, misc;
size_t last_bar = line.find_last_of('|');
if(last_bar == string::npos) continue;
if(last_bar < line.length())
misc = line.substr(last_bar+1);
line.erase(last_bar);
last_bar = line.find_last_of('|');
if(last_bar == string::npos) continue;
if(last_bar < line.length())
url = line.substr(last_bar+1);
line.erase(last_bar);
last_bar = line.find_last_of('|');
if(last_bar == string::npos) continue;
if(last_bar < line.length())
realname = line.substr(last_bar+1);
line.erase(last_bar);
hgname = line;
// remove the example line
if(hgname.find("MercurialName") != string::npos) continue;
list<contributor>::iterator it;
for(it=contributors_list.begin(); it != contributors_list.end() && it->name != hgname; ++it)
{}
if(it == contributors_list.end())
{
contributor c;
c.name = realname;
c.url = url;
c.misc = misc;
contributors_list.push_back(c);
}
else
{
it->name = realname;
it->url = url;
it->misc = misc;
}
}
}
int main()
{
// parse the hg churn output files
map<string,int> contributors_map_for_changedlines = contributors_map_from_churn_output("churn-changedlines.out");
//map<string,int> contributors_map_for_changesets = contributors_map_from_churn_output("churn-changesets.out");
// merge into the contributors list
list<contributor> contributors_list;
map<string,int>::iterator it;
for(it=contributors_map_for_changedlines.begin(); it != contributors_map_for_changedlines.end(); ++it)
{
contributor c;
c.name = it->first;
c.changedlines = it->second;
c.changesets = 0; //contributors_map_for_changesets.find(it->first)->second;
contributors_list.push_back(c);
}
add_online_info_into_contributors_list(contributors_list, "online-info.out");
contributors_list.sort();
cout << "{| cellpadding=\"5\"\n";
cout << "!\n";
cout << "! Lines changed\n";
cout << "!\n";
list<contributor>::iterator itc;
int i = 0;
for(itc=contributors_list.begin(); itc != contributors_list.end(); ++itc)
{
if(itc->name.length() == 0) continue;
if(i%2) cout << "|-\n";
else cout << "|- style=\"background:#FFFFD0\"\n";
if(itc->url.length())
cout << "| [" << itc->url << " " << itc->name << "]\n";
else
cout << "| " << itc->name << "\n";
if(itc->changedlines)
cout << "| " << itc->changedlines << "\n";
else
cout << "| (no information)\n";
cout << "| " << itc->misc << "\n";
i++;
}
cout << "|}" << endl;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/scripts/relicense.py | .py | 2,368 | 70 | # This file is part of Eigen, a lightweight C++ template library
# for linear algebra.
#
# Copyright (C) 2012 Keir Mierle <mierle@gmail.com>
#
# This Source Code Form is subject to the terms of the Mozilla
# Public License v. 2.0. If a copy of the MPL was not distributed
# with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
#
# Author: mierle@gmail.com (Keir Mierle)
#
# Make the long-awaited conversion to MPL.
lgpl3_header = '''
// Eigen is free software; you can redistribute it and/or
// modify it under the terms of the GNU Lesser General Public
// License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
'''
mpl2_header = """
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
"""
import os
import sys
exclusions = set(['relicense.py'])
def update(text):
if text.find(lgpl3_header) == -1:
return text, False
return text.replace(lgpl3_header, mpl2_header), True
rootdir = sys.argv[1]
for root, sub_folders, files in os.walk(rootdir):
for basename in files:
if basename in exclusions:
print 'SKIPPED', filename
continue
filename = os.path.join(root, basename)
fo = file(filename)
text = fo.read()
fo.close()
text, updated = update(text)
if updated:
fo = file(filename, "w")
fo.write(text)
fo.close()
print 'UPDATED', filename
else:
print ' ', filename
| Python |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/bench_sum.cpp | .cpp | 320 | 19 | #include <iostream>
#include <Eigen/Core>
using namespace Eigen;
using namespace std;
int main()
{
typedef Matrix<SCALAR,Eigen::Dynamic,1> Vec;
Vec v(SIZE);
v.setZero();
v[0] = 1;
v[1] = 2;
for(int i = 0; i < 1000000; i++)
{
v.coeffRef(0) += v.sum() * SCALAR(1e-20);
}
cout << v.sum() << endl;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/quat_slerp.cpp | .cpp | 6,006 | 248 |
#include <iostream>
#include <Eigen/Geometry>
#include <bench/BenchTimer.h>
using namespace Eigen;
using namespace std;
template<typename Q>
EIGEN_DONT_INLINE Q nlerp(const Q& a, const Q& b, typename Q::Scalar t)
{
return Q((a.coeffs() * (1.0-t) + b.coeffs() * t).normalized());
}
template<typename Q>
EIGEN_DONT_INLINE Q slerp_eigen(const Q& a, const Q& b, typename Q::Scalar t)
{
return a.slerp(t,b);
}
template<typename Q>
EIGEN_DONT_INLINE Q slerp_legacy(const Q& a, const Q& b, typename Q::Scalar t)
{
typedef typename Q::Scalar Scalar;
static const Scalar one = Scalar(1) - dummy_precision<Scalar>();
Scalar d = a.dot(b);
Scalar absD = internal::abs(d);
if (absD>=one)
return a;
// theta is the angle between the 2 quaternions
Scalar theta = std::acos(absD);
Scalar sinTheta = internal::sin(theta);
Scalar scale0 = internal::sin( ( Scalar(1) - t ) * theta) / sinTheta;
Scalar scale1 = internal::sin( ( t * theta) ) / sinTheta;
if (d<0)
scale1 = -scale1;
return Q(scale0 * a.coeffs() + scale1 * b.coeffs());
}
template<typename Q>
EIGEN_DONT_INLINE Q slerp_legacy_nlerp(const Q& a, const Q& b, typename Q::Scalar t)
{
typedef typename Q::Scalar Scalar;
static const Scalar one = Scalar(1) - epsilon<Scalar>();
Scalar d = a.dot(b);
Scalar absD = internal::abs(d);
Scalar scale0;
Scalar scale1;
if (absD>=one)
{
scale0 = Scalar(1) - t;
scale1 = t;
}
else
{
// theta is the angle between the 2 quaternions
Scalar theta = std::acos(absD);
Scalar sinTheta = internal::sin(theta);
scale0 = internal::sin( ( Scalar(1) - t ) * theta) / sinTheta;
scale1 = internal::sin( ( t * theta) ) / sinTheta;
if (d<0)
scale1 = -scale1;
}
return Q(scale0 * a.coeffs() + scale1 * b.coeffs());
}
template<typename T>
inline T sin_over_x(T x)
{
if (T(1) + x*x == T(1))
return T(1);
else
return std::sin(x)/x;
}
template<typename Q>
EIGEN_DONT_INLINE Q slerp_rw(const Q& a, const Q& b, typename Q::Scalar t)
{
typedef typename Q::Scalar Scalar;
Scalar d = a.dot(b);
Scalar theta;
if (d<0.0)
theta = /*M_PI -*/ Scalar(2)*std::asin( (a.coeffs()+b.coeffs()).norm()/2 );
else
theta = Scalar(2)*std::asin( (a.coeffs()-b.coeffs()).norm()/2 );
// theta is the angle between the 2 quaternions
// Scalar theta = std::acos(absD);
Scalar sinOverTheta = sin_over_x(theta);
Scalar scale0 = (Scalar(1)-t)*sin_over_x( ( Scalar(1) - t ) * theta) / sinOverTheta;
Scalar scale1 = t * sin_over_x( ( t * theta) ) / sinOverTheta;
if (d<0)
scale1 = -scale1;
return Quaternion<Scalar>(scale0 * a.coeffs() + scale1 * b.coeffs());
}
template<typename Q>
EIGEN_DONT_INLINE Q slerp_gael(const Q& a, const Q& b, typename Q::Scalar t)
{
typedef typename Q::Scalar Scalar;
Scalar d = a.dot(b);
Scalar theta;
// theta = Scalar(2) * atan2((a.coeffs()-b.coeffs()).norm(),(a.coeffs()+b.coeffs()).norm());
// if (d<0.0)
// theta = M_PI-theta;
if (d<0.0)
theta = /*M_PI -*/ Scalar(2)*std::asin( (-a.coeffs()-b.coeffs()).norm()/2 );
else
theta = Scalar(2)*std::asin( (a.coeffs()-b.coeffs()).norm()/2 );
Scalar scale0;
Scalar scale1;
if(theta*theta-Scalar(6)==-Scalar(6))
{
scale0 = Scalar(1) - t;
scale1 = t;
}
else
{
Scalar sinTheta = std::sin(theta);
scale0 = internal::sin( ( Scalar(1) - t ) * theta) / sinTheta;
scale1 = internal::sin( ( t * theta) ) / sinTheta;
if (d<0)
scale1 = -scale1;
}
return Quaternion<Scalar>(scale0 * a.coeffs() + scale1 * b.coeffs());
}
int main()
{
typedef double RefScalar;
typedef float TestScalar;
typedef Quaternion<RefScalar> Qd;
typedef Quaternion<TestScalar> Qf;
unsigned int g_seed = (unsigned int) time(NULL);
std::cout << g_seed << "\n";
// g_seed = 1259932496;
srand(g_seed);
Matrix<RefScalar,Dynamic,1> maxerr(7);
maxerr.setZero();
Matrix<RefScalar,Dynamic,1> avgerr(7);
avgerr.setZero();
cout << "double=>float=>double nlerp eigen legacy(snap) legacy(nlerp) rightway gael's criteria\n";
int rep = 100;
int iters = 40;
for (int w=0; w<rep; ++w)
{
Qf a, b;
a.coeffs().setRandom();
a.normalize();
b.coeffs().setRandom();
b.normalize();
Qf c[6];
Qd ar(a.cast<RefScalar>());
Qd br(b.cast<RefScalar>());
Qd cr;
cout.precision(8);
cout << std::scientific;
for (int i=0; i<iters; ++i)
{
RefScalar t = 0.65;
cr = slerp_rw(ar,br,t);
Qf refc = cr.cast<TestScalar>();
c[0] = nlerp(a,b,t);
c[1] = slerp_eigen(a,b,t);
c[2] = slerp_legacy(a,b,t);
c[3] = slerp_legacy_nlerp(a,b,t);
c[4] = slerp_rw(a,b,t);
c[5] = slerp_gael(a,b,t);
VectorXd err(7);
err[0] = (cr.coeffs()-refc.cast<RefScalar>().coeffs()).norm();
// std::cout << err[0] << " ";
for (int k=0; k<6; ++k)
{
err[k+1] = (c[k].coeffs()-refc.coeffs()).norm();
// std::cout << err[k+1] << " ";
}
maxerr = maxerr.cwise().max(err);
avgerr += err;
// std::cout << "\n";
b = cr.cast<TestScalar>();
br = cr;
}
// std::cout << "\n";
}
avgerr /= RefScalar(rep*iters);
cout << "\n\nAccuracy:\n"
<< " max: " << maxerr.transpose() << "\n";
cout << " avg: " << avgerr.transpose() << "\n";
// perf bench
Quaternionf a,b;
a.coeffs().setRandom();
a.normalize();
b.coeffs().setRandom();
b.normalize();
//b = a;
float s = 0.65;
#define BENCH(FUNC) {\
BenchTimer t; \
for(int k=0; k<2; ++k) {\
t.start(); \
for(int i=0; i<1000000; ++i) \
FUNC(a,b,s); \
t.stop(); \
} \
cout << " " << #FUNC << " => \t " << t.value() << "s\n"; \
}
cout << "\nSpeed:\n" << std::fixed;
BENCH(nlerp);
BENCH(slerp_eigen);
BENCH(slerp_legacy);
BENCH(slerp_legacy_nlerp);
BENCH(slerp_rw);
BENCH(slerp_gael);
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/BenchSparseUtil.h | .h | 3,932 | 150 |
#include <Eigen/Sparse>
#include <bench/BenchTimer.h>
#include <set>
using namespace std;
using namespace Eigen;
using namespace Eigen;
#ifndef SIZE
#define SIZE 1024
#endif
#ifndef DENSITY
#define DENSITY 0.01
#endif
#ifndef SCALAR
#define SCALAR double
#endif
typedef SCALAR Scalar;
typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
typedef Matrix<Scalar,Dynamic,1> DenseVector;
typedef SparseMatrix<Scalar> EigenSparseMatrix;
void fillMatrix(float density, int rows, int cols, EigenSparseMatrix& dst)
{
dst.reserve(double(rows)*cols*density);
for(int j = 0; j < cols; j++)
{
for(int i = 0; i < rows; i++)
{
Scalar v = (internal::random<float>(0,1) < density) ? internal::random<Scalar>() : 0;
if (v!=0)
dst.insert(i,j) = v;
}
}
dst.finalize();
}
void fillMatrix2(int nnzPerCol, int rows, int cols, EigenSparseMatrix& dst)
{
// std::cout << "alloc " << nnzPerCol*cols << "\n";
dst.reserve(nnzPerCol*cols);
for(int j = 0; j < cols; j++)
{
std::set<int> aux;
for(int i = 0; i < nnzPerCol; i++)
{
int k = internal::random<int>(0,rows-1);
while (aux.find(k)!=aux.end())
k = internal::random<int>(0,rows-1);
aux.insert(k);
dst.insert(k,j) = internal::random<Scalar>();
}
}
dst.finalize();
}
void eiToDense(const EigenSparseMatrix& src, DenseMatrix& dst)
{
dst.setZero();
for (int j=0; j<src.cols(); ++j)
for (EigenSparseMatrix::InnerIterator it(src.derived(), j); it; ++it)
dst(it.index(),j) = it.value();
}
#ifndef NOGMM
#include "gmm/gmm.h"
typedef gmm::csc_matrix<Scalar> GmmSparse;
typedef gmm::col_matrix< gmm::wsvector<Scalar> > GmmDynSparse;
void eiToGmm(const EigenSparseMatrix& src, GmmSparse& dst)
{
GmmDynSparse tmp(src.rows(), src.cols());
for (int j=0; j<src.cols(); ++j)
for (EigenSparseMatrix::InnerIterator it(src.derived(), j); it; ++it)
tmp(it.index(),j) = it.value();
gmm::copy(tmp, dst);
}
#endif
#ifndef NOMTL
#include <boost/numeric/mtl/mtl.hpp>
typedef mtl::compressed2D<Scalar, mtl::matrix::parameters<mtl::tag::col_major> > MtlSparse;
typedef mtl::compressed2D<Scalar, mtl::matrix::parameters<mtl::tag::row_major> > MtlSparseRowMajor;
void eiToMtl(const EigenSparseMatrix& src, MtlSparse& dst)
{
mtl::matrix::inserter<MtlSparse> ins(dst);
for (int j=0; j<src.cols(); ++j)
for (EigenSparseMatrix::InnerIterator it(src.derived(), j); it; ++it)
ins[it.index()][j] = it.value();
}
#endif
#ifdef CSPARSE
extern "C" {
#include "cs.h"
}
void eiToCSparse(const EigenSparseMatrix& src, cs* &dst)
{
cs* aux = cs_spalloc (0, 0, 1, 1, 1);
for (int j=0; j<src.cols(); ++j)
for (EigenSparseMatrix::InnerIterator it(src.derived(), j); it; ++it)
if (!cs_entry(aux, it.index(), j, it.value()))
{
std::cout << "cs_entry error\n";
exit(2);
}
dst = cs_compress(aux);
// cs_spfree(aux);
}
#endif // CSPARSE
#ifndef NOUBLAS
#include <boost/numeric/ublas/vector.hpp>
#include <boost/numeric/ublas/matrix.hpp>
#include <boost/numeric/ublas/io.hpp>
#include <boost/numeric/ublas/triangular.hpp>
#include <boost/numeric/ublas/vector_sparse.hpp>
#include <boost/numeric/ublas/matrix_sparse.hpp>
#include <boost/numeric/ublas/vector_of_vector.hpp>
#include <boost/numeric/ublas/operation.hpp>
typedef boost::numeric::ublas::compressed_matrix<Scalar,boost::numeric::ublas::column_major> UBlasSparse;
void eiToUblas(const EigenSparseMatrix& src, UBlasSparse& dst)
{
dst.resize(src.rows(), src.cols(), false);
for (int j=0; j<src.cols(); ++j)
for (EigenSparseMatrix::InnerIterator it(src.derived(), j); it; ++it)
dst(it.index(),j) = it.value();
}
template <typename EigenType, typename UblasType>
void eiToUblasVec(const EigenType& src, UblasType& dst)
{
dst.resize(src.size());
for (int j=0; j<src.size(); ++j)
dst[j] = src.coeff(j);
}
#endif
#ifdef OSKI
extern "C" {
#include <oski/oski.h>
}
#endif
| Unknown |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/BenchTimer.h | .h | 4,392 | 196 | // This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
#ifndef EIGEN_BENCH_TIMERR_H
#define EIGEN_BENCH_TIMERR_H
#if defined(_WIN32) || defined(__CYGWIN__)
# ifndef NOMINMAX
# define NOMINMAX
# define EIGEN_BT_UNDEF_NOMINMAX
# endif
# ifndef WIN32_LEAN_AND_MEAN
# define WIN32_LEAN_AND_MEAN
# define EIGEN_BT_UNDEF_WIN32_LEAN_AND_MEAN
# endif
# include <windows.h>
#elif defined(__APPLE__)
#include <mach/mach_time.h>
#else
# include <unistd.h>
#endif
static void escape(void *p) {
asm volatile("" : : "g"(p) : "memory");
}
static void clobber() {
asm volatile("" : : : "memory");
}
#include <Eigen/Core>
namespace Eigen
{
enum {
CPU_TIMER = 0,
REAL_TIMER = 1
};
/** Elapsed time timer keeping the best try.
*
* On POSIX platforms we use clock_gettime with CLOCK_PROCESS_CPUTIME_ID.
* On Windows we use QueryPerformanceCounter
*
* Important: on linux, you must link with -lrt
*/
class BenchTimer
{
public:
BenchTimer()
{
#if defined(_WIN32) || defined(__CYGWIN__)
LARGE_INTEGER freq;
QueryPerformanceFrequency(&freq);
m_frequency = (double)freq.QuadPart;
#endif
reset();
}
~BenchTimer() {}
inline void reset()
{
m_bests.fill(1e9);
m_worsts.fill(0);
m_totals.setZero();
}
inline void start()
{
m_starts[CPU_TIMER] = getCpuTime();
m_starts[REAL_TIMER] = getRealTime();
}
inline void stop()
{
m_times[CPU_TIMER] = getCpuTime() - m_starts[CPU_TIMER];
m_times[REAL_TIMER] = getRealTime() - m_starts[REAL_TIMER];
#if EIGEN_VERSION_AT_LEAST(2,90,0)
m_bests = m_bests.cwiseMin(m_times);
m_worsts = m_worsts.cwiseMax(m_times);
#else
m_bests(0) = std::min(m_bests(0),m_times(0));
m_bests(1) = std::min(m_bests(1),m_times(1));
m_worsts(0) = std::max(m_worsts(0),m_times(0));
m_worsts(1) = std::max(m_worsts(1),m_times(1));
#endif
m_totals += m_times;
}
/** Return the elapsed time in seconds between the last start/stop pair
*/
inline double value(int TIMER = CPU_TIMER) const
{
return m_times[TIMER];
}
/** Return the best elapsed time in seconds
*/
inline double best(int TIMER = CPU_TIMER) const
{
return m_bests[TIMER];
}
/** Return the worst elapsed time in seconds
*/
inline double worst(int TIMER = CPU_TIMER) const
{
return m_worsts[TIMER];
}
/** Return the total elapsed time in seconds.
*/
inline double total(int TIMER = CPU_TIMER) const
{
return m_totals[TIMER];
}
inline double getCpuTime() const
{
#ifdef _WIN32
LARGE_INTEGER query_ticks;
QueryPerformanceCounter(&query_ticks);
return query_ticks.QuadPart/m_frequency;
#elif __APPLE__
return double(mach_absolute_time())*1e-9;
#else
timespec ts;
clock_gettime(CLOCK_PROCESS_CPUTIME_ID, &ts);
return double(ts.tv_sec) + 1e-9 * double(ts.tv_nsec);
#endif
}
inline double getRealTime() const
{
#ifdef _WIN32
SYSTEMTIME st;
GetSystemTime(&st);
return (double)st.wSecond + 1.e-3 * (double)st.wMilliseconds;
#elif __APPLE__
return double(mach_absolute_time())*1e-9;
#else
timespec ts;
clock_gettime(CLOCK_REALTIME, &ts);
return double(ts.tv_sec) + 1e-9 * double(ts.tv_nsec);
#endif
}
protected:
#if defined(_WIN32) || defined(__CYGWIN__)
double m_frequency;
#endif
Vector2d m_starts;
Vector2d m_times;
Vector2d m_bests;
Vector2d m_worsts;
Vector2d m_totals;
public:
EIGEN_MAKE_ALIGNED_OPERATOR_NEW
};
#define BENCH(TIMER,TRIES,REP,CODE) { \
TIMER.reset(); \
for(int uglyvarname1=0; uglyvarname1<TRIES; ++uglyvarname1){ \
TIMER.start(); \
for(int uglyvarname2=0; uglyvarname2<REP; ++uglyvarname2){ \
CODE; \
} \
TIMER.stop(); \
clobber(); \
} \
}
}
// clean #defined tokens
#ifdef EIGEN_BT_UNDEF_NOMINMAX
# undef EIGEN_BT_UNDEF_NOMINMAX
# undef NOMINMAX
#endif
#ifdef EIGEN_BT_UNDEF_WIN32_LEAN_AND_MEAN
# undef EIGEN_BT_UNDEF_WIN32_LEAN_AND_MEAN
# undef WIN32_LEAN_AND_MEAN
#endif
#endif // EIGEN_BENCH_TIMERR_H
| Unknown |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/sparse_setter.cpp | .cpp | 13,761 | 486 |
//g++ -O3 -g0 -DNDEBUG sparse_product.cpp -I.. -I/home/gael/Coding/LinearAlgebra/mtl4/ -DDENSITY=0.005 -DSIZE=10000 && ./a.out
//g++ -O3 -g0 -DNDEBUG sparse_product.cpp -I.. -I/home/gael/Coding/LinearAlgebra/mtl4/ -DDENSITY=0.05 -DSIZE=2000 && ./a.out
// -DNOGMM -DNOMTL -DCSPARSE
// -I /home/gael/Coding/LinearAlgebra/CSparse/Include/ /home/gael/Coding/LinearAlgebra/CSparse/Lib/libcsparse.a
#ifndef SIZE
#define SIZE 100000
#endif
#ifndef NBPERROW
#define NBPERROW 24
#endif
#ifndef REPEAT
#define REPEAT 2
#endif
#ifndef NBTRIES
#define NBTRIES 2
#endif
#ifndef KK
#define KK 10
#endif
#ifndef NOGOOGLE
#define EIGEN_GOOGLEHASH_SUPPORT
#include <google/sparse_hash_map>
#endif
#include "BenchSparseUtil.h"
#define CHECK_MEM
// #define CHECK_MEM std/**/::cout << "check mem\n"; getchar();
#define BENCH(X) \
timer.reset(); \
for (int _j=0; _j<NBTRIES; ++_j) { \
timer.start(); \
for (int _k=0; _k<REPEAT; ++_k) { \
X \
} timer.stop(); }
typedef std::vector<Vector2i> Coordinates;
typedef std::vector<float> Values;
EIGEN_DONT_INLINE Scalar* setinnerrand_eigen(const Coordinates& coords, const Values& vals);
EIGEN_DONT_INLINE Scalar* setrand_eigen_dynamic(const Coordinates& coords, const Values& vals);
EIGEN_DONT_INLINE Scalar* setrand_eigen_compact(const Coordinates& coords, const Values& vals);
EIGEN_DONT_INLINE Scalar* setrand_eigen_sumeq(const Coordinates& coords, const Values& vals);
EIGEN_DONT_INLINE Scalar* setrand_eigen_gnu_hash(const Coordinates& coords, const Values& vals);
EIGEN_DONT_INLINE Scalar* setrand_eigen_google_dense(const Coordinates& coords, const Values& vals);
EIGEN_DONT_INLINE Scalar* setrand_eigen_google_sparse(const Coordinates& coords, const Values& vals);
EIGEN_DONT_INLINE Scalar* setrand_scipy(const Coordinates& coords, const Values& vals);
EIGEN_DONT_INLINE Scalar* setrand_ublas_mapped(const Coordinates& coords, const Values& vals);
EIGEN_DONT_INLINE Scalar* setrand_ublas_coord(const Coordinates& coords, const Values& vals);
EIGEN_DONT_INLINE Scalar* setrand_ublas_compressed(const Coordinates& coords, const Values& vals);
EIGEN_DONT_INLINE Scalar* setrand_ublas_genvec(const Coordinates& coords, const Values& vals);
EIGEN_DONT_INLINE Scalar* setrand_mtl(const Coordinates& coords, const Values& vals);
int main(int argc, char *argv[])
{
int rows = SIZE;
int cols = SIZE;
bool fullyrand = true;
BenchTimer timer;
Coordinates coords;
Values values;
if(fullyrand)
{
Coordinates pool;
pool.reserve(cols*NBPERROW);
std::cerr << "fill pool" << "\n";
for (int i=0; i<cols*NBPERROW; )
{
// DynamicSparseMatrix<int> stencil(SIZE,SIZE);
Vector2i ij(internal::random<int>(0,rows-1),internal::random<int>(0,cols-1));
// if(stencil.coeffRef(ij.x(), ij.y())==0)
{
// stencil.coeffRef(ij.x(), ij.y()) = 1;
pool.push_back(ij);
}
++i;
}
std::cerr << "pool ok" << "\n";
int n = cols*NBPERROW*KK;
coords.reserve(n);
values.reserve(n);
for (int i=0; i<n; ++i)
{
int i = internal::random<int>(0,pool.size());
coords.push_back(pool[i]);
values.push_back(internal::random<Scalar>());
}
}
else
{
for (int j=0; j<cols; ++j)
for (int i=0; i<NBPERROW; ++i)
{
coords.push_back(Vector2i(internal::random<int>(0,rows-1),j));
values.push_back(internal::random<Scalar>());
}
}
std::cout << "nnz = " << coords.size() << "\n";
CHECK_MEM
// dense matrices
#ifdef DENSEMATRIX
{
BENCH(setrand_eigen_dense(coords,values);)
std::cout << "Eigen Dense\t" << timer.value() << "\n";
}
#endif
// eigen sparse matrices
// if (!fullyrand)
// {
// BENCH(setinnerrand_eigen(coords,values);)
// std::cout << "Eigen fillrand\t" << timer.value() << "\n";
// }
{
BENCH(setrand_eigen_dynamic(coords,values);)
std::cout << "Eigen dynamic\t" << timer.value() << "\n";
}
// {
// BENCH(setrand_eigen_compact(coords,values);)
// std::cout << "Eigen compact\t" << timer.value() << "\n";
// }
{
BENCH(setrand_eigen_sumeq(coords,values);)
std::cout << "Eigen sumeq\t" << timer.value() << "\n";
}
{
// BENCH(setrand_eigen_gnu_hash(coords,values);)
// std::cout << "Eigen std::map\t" << timer.value() << "\n";
}
{
BENCH(setrand_scipy(coords,values);)
std::cout << "scipy\t" << timer.value() << "\n";
}
#ifndef NOGOOGLE
{
BENCH(setrand_eigen_google_dense(coords,values);)
std::cout << "Eigen google dense\t" << timer.value() << "\n";
}
{
BENCH(setrand_eigen_google_sparse(coords,values);)
std::cout << "Eigen google sparse\t" << timer.value() << "\n";
}
#endif
#ifndef NOUBLAS
{
// BENCH(setrand_ublas_mapped(coords,values);)
// std::cout << "ublas mapped\t" << timer.value() << "\n";
}
{
BENCH(setrand_ublas_genvec(coords,values);)
std::cout << "ublas vecofvec\t" << timer.value() << "\n";
}
/*{
timer.reset();
timer.start();
for (int k=0; k<REPEAT; ++k)
setrand_ublas_compressed(coords,values);
timer.stop();
std::cout << "ublas comp\t" << timer.value() << "\n";
}
{
timer.reset();
timer.start();
for (int k=0; k<REPEAT; ++k)
setrand_ublas_coord(coords,values);
timer.stop();
std::cout << "ublas coord\t" << timer.value() << "\n";
}*/
#endif
// MTL4
#ifndef NOMTL
{
BENCH(setrand_mtl(coords,values));
std::cout << "MTL\t" << timer.value() << "\n";
}
#endif
return 0;
}
EIGEN_DONT_INLINE Scalar* setinnerrand_eigen(const Coordinates& coords, const Values& vals)
{
using namespace Eigen;
SparseMatrix<Scalar> mat(SIZE,SIZE);
//mat.startFill(2000000/*coords.size()*/);
for (int i=0; i<coords.size(); ++i)
{
mat.insert(coords[i].x(), coords[i].y()) = vals[i];
}
mat.finalize();
CHECK_MEM;
return 0;
}
EIGEN_DONT_INLINE Scalar* setrand_eigen_dynamic(const Coordinates& coords, const Values& vals)
{
using namespace Eigen;
DynamicSparseMatrix<Scalar> mat(SIZE,SIZE);
mat.reserve(coords.size()/10);
for (int i=0; i<coords.size(); ++i)
{
mat.coeffRef(coords[i].x(), coords[i].y()) += vals[i];
}
mat.finalize();
CHECK_MEM;
return &mat.coeffRef(coords[0].x(), coords[0].y());
}
EIGEN_DONT_INLINE Scalar* setrand_eigen_sumeq(const Coordinates& coords, const Values& vals)
{
using namespace Eigen;
int n = coords.size()/KK;
DynamicSparseMatrix<Scalar> mat(SIZE,SIZE);
for (int j=0; j<KK; ++j)
{
DynamicSparseMatrix<Scalar> aux(SIZE,SIZE);
mat.reserve(n);
for (int i=j*n; i<(j+1)*n; ++i)
{
aux.insert(coords[i].x(), coords[i].y()) += vals[i];
}
aux.finalize();
mat += aux;
}
return &mat.coeffRef(coords[0].x(), coords[0].y());
}
EIGEN_DONT_INLINE Scalar* setrand_eigen_compact(const Coordinates& coords, const Values& vals)
{
using namespace Eigen;
DynamicSparseMatrix<Scalar> setter(SIZE,SIZE);
setter.reserve(coords.size()/10);
for (int i=0; i<coords.size(); ++i)
{
setter.coeffRef(coords[i].x(), coords[i].y()) += vals[i];
}
SparseMatrix<Scalar> mat = setter;
CHECK_MEM;
return &mat.coeffRef(coords[0].x(), coords[0].y());
}
EIGEN_DONT_INLINE Scalar* setrand_eigen_gnu_hash(const Coordinates& coords, const Values& vals)
{
using namespace Eigen;
SparseMatrix<Scalar> mat(SIZE,SIZE);
{
RandomSetter<SparseMatrix<Scalar>, StdMapTraits > setter(mat);
for (int i=0; i<coords.size(); ++i)
{
setter(coords[i].x(), coords[i].y()) += vals[i];
}
CHECK_MEM;
}
return &mat.coeffRef(coords[0].x(), coords[0].y());
}
#ifndef NOGOOGLE
EIGEN_DONT_INLINE Scalar* setrand_eigen_google_dense(const Coordinates& coords, const Values& vals)
{
using namespace Eigen;
SparseMatrix<Scalar> mat(SIZE,SIZE);
{
RandomSetter<SparseMatrix<Scalar>, GoogleDenseHashMapTraits> setter(mat);
for (int i=0; i<coords.size(); ++i)
setter(coords[i].x(), coords[i].y()) += vals[i];
CHECK_MEM;
}
return &mat.coeffRef(coords[0].x(), coords[0].y());
}
EIGEN_DONT_INLINE Scalar* setrand_eigen_google_sparse(const Coordinates& coords, const Values& vals)
{
using namespace Eigen;
SparseMatrix<Scalar> mat(SIZE,SIZE);
{
RandomSetter<SparseMatrix<Scalar>, GoogleSparseHashMapTraits> setter(mat);
for (int i=0; i<coords.size(); ++i)
setter(coords[i].x(), coords[i].y()) += vals[i];
CHECK_MEM;
}
return &mat.coeffRef(coords[0].x(), coords[0].y());
}
#endif
template <class T>
void coo_tocsr(const int n_row,
const int n_col,
const int nnz,
const Coordinates Aij,
const Values Ax,
int Bp[],
int Bj[],
T Bx[])
{
//compute number of non-zero entries per row of A coo_tocsr
std::fill(Bp, Bp + n_row, 0);
for (int n = 0; n < nnz; n++){
Bp[Aij[n].x()]++;
}
//cumsum the nnz per row to get Bp[]
for(int i = 0, cumsum = 0; i < n_row; i++){
int temp = Bp[i];
Bp[i] = cumsum;
cumsum += temp;
}
Bp[n_row] = nnz;
//write Aj,Ax into Bj,Bx
for(int n = 0; n < nnz; n++){
int row = Aij[n].x();
int dest = Bp[row];
Bj[dest] = Aij[n].y();
Bx[dest] = Ax[n];
Bp[row]++;
}
for(int i = 0, last = 0; i <= n_row; i++){
int temp = Bp[i];
Bp[i] = last;
last = temp;
}
//now Bp,Bj,Bx form a CSR representation (with possible duplicates)
}
template< class T1, class T2 >
bool kv_pair_less(const std::pair<T1,T2>& x, const std::pair<T1,T2>& y){
return x.first < y.first;
}
template<class I, class T>
void csr_sort_indices(const I n_row,
const I Ap[],
I Aj[],
T Ax[])
{
std::vector< std::pair<I,T> > temp;
for(I i = 0; i < n_row; i++){
I row_start = Ap[i];
I row_end = Ap[i+1];
temp.clear();
for(I jj = row_start; jj < row_end; jj++){
temp.push_back(std::make_pair(Aj[jj],Ax[jj]));
}
std::sort(temp.begin(),temp.end(),kv_pair_less<I,T>);
for(I jj = row_start, n = 0; jj < row_end; jj++, n++){
Aj[jj] = temp[n].first;
Ax[jj] = temp[n].second;
}
}
}
template <class I, class T>
void csr_sum_duplicates(const I n_row,
const I n_col,
I Ap[],
I Aj[],
T Ax[])
{
I nnz = 0;
I row_end = 0;
for(I i = 0; i < n_row; i++){
I jj = row_end;
row_end = Ap[i+1];
while( jj < row_end ){
I j = Aj[jj];
T x = Ax[jj];
jj++;
while( jj < row_end && Aj[jj] == j ){
x += Ax[jj];
jj++;
}
Aj[nnz] = j;
Ax[nnz] = x;
nnz++;
}
Ap[i+1] = nnz;
}
}
EIGEN_DONT_INLINE Scalar* setrand_scipy(const Coordinates& coords, const Values& vals)
{
using namespace Eigen;
SparseMatrix<Scalar> mat(SIZE,SIZE);
mat.resizeNonZeros(coords.size());
// std::cerr << "setrand_scipy...\n";
coo_tocsr<Scalar>(SIZE,SIZE, coords.size(), coords, vals, mat._outerIndexPtr(), mat._innerIndexPtr(), mat._valuePtr());
// std::cerr << "coo_tocsr ok\n";
csr_sort_indices(SIZE, mat._outerIndexPtr(), mat._innerIndexPtr(), mat._valuePtr());
csr_sum_duplicates(SIZE, SIZE, mat._outerIndexPtr(), mat._innerIndexPtr(), mat._valuePtr());
mat.resizeNonZeros(mat._outerIndexPtr()[SIZE]);
return &mat.coeffRef(coords[0].x(), coords[0].y());
}
#ifndef NOUBLAS
EIGEN_DONT_INLINE Scalar* setrand_ublas_mapped(const Coordinates& coords, const Values& vals)
{
using namespace boost;
using namespace boost::numeric;
using namespace boost::numeric::ublas;
mapped_matrix<Scalar> aux(SIZE,SIZE);
for (int i=0; i<coords.size(); ++i)
{
aux(coords[i].x(), coords[i].y()) += vals[i];
}
CHECK_MEM;
compressed_matrix<Scalar> mat(aux);
return 0;// &mat(coords[0].x(), coords[0].y());
}
/*EIGEN_DONT_INLINE Scalar* setrand_ublas_coord(const Coordinates& coords, const Values& vals)
{
using namespace boost;
using namespace boost::numeric;
using namespace boost::numeric::ublas;
coordinate_matrix<Scalar> aux(SIZE,SIZE);
for (int i=0; i<coords.size(); ++i)
{
aux(coords[i].x(), coords[i].y()) = vals[i];
}
compressed_matrix<Scalar> mat(aux);
return 0;//&mat(coords[0].x(), coords[0].y());
}
EIGEN_DONT_INLINE Scalar* setrand_ublas_compressed(const Coordinates& coords, const Values& vals)
{
using namespace boost;
using namespace boost::numeric;
using namespace boost::numeric::ublas;
compressed_matrix<Scalar> mat(SIZE,SIZE);
for (int i=0; i<coords.size(); ++i)
{
mat(coords[i].x(), coords[i].y()) = vals[i];
}
return 0;//&mat(coords[0].x(), coords[0].y());
}*/
EIGEN_DONT_INLINE Scalar* setrand_ublas_genvec(const Coordinates& coords, const Values& vals)
{
using namespace boost;
using namespace boost::numeric;
using namespace boost::numeric::ublas;
// ublas::vector<coordinate_vector<Scalar> > foo;
generalized_vector_of_vector<Scalar, row_major, ublas::vector<coordinate_vector<Scalar> > > aux(SIZE,SIZE);
for (int i=0; i<coords.size(); ++i)
{
aux(coords[i].x(), coords[i].y()) += vals[i];
}
CHECK_MEM;
compressed_matrix<Scalar,row_major> mat(aux);
return 0;//&mat(coords[0].x(), coords[0].y());
}
#endif
#ifndef NOMTL
EIGEN_DONT_INLINE void setrand_mtl(const Coordinates& coords, const Values& vals);
#endif
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/basicbenchmark.h | .h | 1,669 | 64 |
#ifndef EIGEN_BENCH_BASICBENCH_H
#define EIGEN_BENCH_BASICBENCH_H
enum {LazyEval, EarlyEval, OmpEval};
template<int Mode, typename MatrixType>
void benchBasic_loop(const MatrixType& I, MatrixType& m, int iterations) __attribute__((noinline));
template<int Mode, typename MatrixType>
void benchBasic_loop(const MatrixType& I, MatrixType& m, int iterations)
{
for(int a = 0; a < iterations; a++)
{
if (Mode==LazyEval)
{
asm("#begin_bench_loop LazyEval");
if (MatrixType::SizeAtCompileTime!=Eigen::Dynamic) asm("#fixedsize");
m = (I + 0.00005 * (m + m.lazy() * m)).eval();
}
else if (Mode==OmpEval)
{
asm("#begin_bench_loop OmpEval");
if (MatrixType::SizeAtCompileTime!=Eigen::Dynamic) asm("#fixedsize");
m = (I + 0.00005 * (m + m.lazy() * m)).evalOMP();
}
else
{
asm("#begin_bench_loop EarlyEval");
if (MatrixType::SizeAtCompileTime!=Eigen::Dynamic) asm("#fixedsize");
m = I + 0.00005 * (m + m * m);
}
asm("#end_bench_loop");
}
}
template<int Mode, typename MatrixType>
double benchBasic(const MatrixType& mat, int size, int tries) __attribute__((noinline));
template<int Mode, typename MatrixType>
double benchBasic(const MatrixType& mat, int iterations, int tries)
{
const int rows = mat.rows();
const int cols = mat.cols();
MatrixType I(rows,cols);
MatrixType m(rows,cols);
initMatrix_identity(I);
Eigen::BenchTimer timer;
for(uint t=0; t<tries; ++t)
{
initMatrix_random(m);
timer.start();
benchBasic_loop<Mode>(I, m, iterations);
timer.stop();
cerr << m;
}
return timer.value();
};
#endif // EIGEN_BENCH_BASICBENCH_H
| Unknown |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/eig33.cpp | .cpp | 7,244 | 196 | // This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2010 Gael Guennebaud <gael.guennebaud@inria.fr>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
// The computeRoots function included in this is based on materials
// covered by the following copyright and license:
//
// Geometric Tools, LLC
// Copyright (c) 1998-2010
// Distributed under the Boost Software License, Version 1.0.
//
// Permission is hereby granted, free of charge, to any person or organization
// obtaining a copy of the software and accompanying documentation covered by
// this license (the "Software") to use, reproduce, display, distribute,
// execute, and transmit the Software, and to prepare derivative works of the
// Software, and to permit third-parties to whom the Software is furnished to
// do so, all subject to the following:
//
// The copyright notices in the Software and this entire statement, including
// the above license grant, this restriction and the following disclaimer,
// must be included in all copies of the Software, in whole or in part, and
// all derivative works of the Software, unless such copies or derivative
// works are solely in the form of machine-executable object code generated by
// a source language processor.
//
// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
// FITNESS FOR A PARTICULAR PURPOSE, TITLE AND NON-INFRINGEMENT. IN NO EVENT
// SHALL THE COPYRIGHT HOLDERS OR ANYONE DISTRIBUTING THE SOFTWARE BE LIABLE
// FOR ANY DAMAGES OR OTHER LIABILITY, WHETHER IN CONTRACT, TORT OR OTHERWISE,
// ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
// DEALINGS IN THE SOFTWARE.
#include <iostream>
#include <Eigen/Core>
#include <Eigen/Eigenvalues>
#include <Eigen/Geometry>
#include <bench/BenchTimer.h>
using namespace Eigen;
using namespace std;
template<typename Matrix, typename Roots>
inline void computeRoots(const Matrix& m, Roots& roots)
{
typedef typename Matrix::Scalar Scalar;
const Scalar s_inv3 = 1.0/3.0;
const Scalar s_sqrt3 = std::sqrt(Scalar(3.0));
// The characteristic equation is x^3 - c2*x^2 + c1*x - c0 = 0. The
// eigenvalues are the roots to this equation, all guaranteed to be
// real-valued, because the matrix is symmetric.
Scalar c0 = m(0,0)*m(1,1)*m(2,2) + Scalar(2)*m(0,1)*m(0,2)*m(1,2) - m(0,0)*m(1,2)*m(1,2) - m(1,1)*m(0,2)*m(0,2) - m(2,2)*m(0,1)*m(0,1);
Scalar c1 = m(0,0)*m(1,1) - m(0,1)*m(0,1) + m(0,0)*m(2,2) - m(0,2)*m(0,2) + m(1,1)*m(2,2) - m(1,2)*m(1,2);
Scalar c2 = m(0,0) + m(1,1) + m(2,2);
// Construct the parameters used in classifying the roots of the equation
// and in solving the equation for the roots in closed form.
Scalar c2_over_3 = c2*s_inv3;
Scalar a_over_3 = (c1 - c2*c2_over_3)*s_inv3;
if (a_over_3 > Scalar(0))
a_over_3 = Scalar(0);
Scalar half_b = Scalar(0.5)*(c0 + c2_over_3*(Scalar(2)*c2_over_3*c2_over_3 - c1));
Scalar q = half_b*half_b + a_over_3*a_over_3*a_over_3;
if (q > Scalar(0))
q = Scalar(0);
// Compute the eigenvalues by solving for the roots of the polynomial.
Scalar rho = std::sqrt(-a_over_3);
Scalar theta = std::atan2(std::sqrt(-q),half_b)*s_inv3;
Scalar cos_theta = std::cos(theta);
Scalar sin_theta = std::sin(theta);
roots(2) = c2_over_3 + Scalar(2)*rho*cos_theta;
roots(0) = c2_over_3 - rho*(cos_theta + s_sqrt3*sin_theta);
roots(1) = c2_over_3 - rho*(cos_theta - s_sqrt3*sin_theta);
}
template<typename Matrix, typename Vector>
void eigen33(const Matrix& mat, Matrix& evecs, Vector& evals)
{
typedef typename Matrix::Scalar Scalar;
// Scale the matrix so its entries are in [-1,1]. The scaling is applied
// only when at least one matrix entry has magnitude larger than 1.
Scalar shift = mat.trace()/3;
Matrix scaledMat = mat;
scaledMat.diagonal().array() -= shift;
Scalar scale = scaledMat.cwiseAbs()/*.template triangularView<Lower>()*/.maxCoeff();
scale = std::max(scale,Scalar(1));
scaledMat/=scale;
// Compute the eigenvalues
// scaledMat.setZero();
computeRoots(scaledMat,evals);
// compute the eigen vectors
// **here we assume 3 differents eigenvalues**
// "optimized version" which appears to be slower with gcc!
// Vector base;
// Scalar alpha, beta;
// base << scaledMat(1,0) * scaledMat(2,1),
// scaledMat(1,0) * scaledMat(2,0),
// -scaledMat(1,0) * scaledMat(1,0);
// for(int k=0; k<2; ++k)
// {
// alpha = scaledMat(0,0) - evals(k);
// beta = scaledMat(1,1) - evals(k);
// evecs.col(k) = (base + Vector(-beta*scaledMat(2,0), -alpha*scaledMat(2,1), alpha*beta)).normalized();
// }
// evecs.col(2) = evecs.col(0).cross(evecs.col(1)).normalized();
// // naive version
// Matrix tmp;
// tmp = scaledMat;
// tmp.diagonal().array() -= evals(0);
// evecs.col(0) = tmp.row(0).cross(tmp.row(1)).normalized();
//
// tmp = scaledMat;
// tmp.diagonal().array() -= evals(1);
// evecs.col(1) = tmp.row(0).cross(tmp.row(1)).normalized();
//
// tmp = scaledMat;
// tmp.diagonal().array() -= evals(2);
// evecs.col(2) = tmp.row(0).cross(tmp.row(1)).normalized();
// a more stable version:
if((evals(2)-evals(0))<=Eigen::NumTraits<Scalar>::epsilon())
{
evecs.setIdentity();
}
else
{
Matrix tmp;
tmp = scaledMat;
tmp.diagonal ().array () -= evals (2);
evecs.col (2) = tmp.row (0).cross (tmp.row (1)).normalized ();
tmp = scaledMat;
tmp.diagonal ().array () -= evals (1);
evecs.col(1) = tmp.row (0).cross(tmp.row (1));
Scalar n1 = evecs.col(1).norm();
if(n1<=Eigen::NumTraits<Scalar>::epsilon())
evecs.col(1) = evecs.col(2).unitOrthogonal();
else
evecs.col(1) /= n1;
// make sure that evecs[1] is orthogonal to evecs[2]
evecs.col(1) = evecs.col(2).cross(evecs.col(1).cross(evecs.col(2))).normalized();
evecs.col(0) = evecs.col(2).cross(evecs.col(1));
}
// Rescale back to the original size.
evals *= scale;
evals.array()+=shift;
}
int main()
{
BenchTimer t;
int tries = 10;
int rep = 400000;
typedef Matrix3d Mat;
typedef Vector3d Vec;
Mat A = Mat::Random(3,3);
A = A.adjoint() * A;
// Mat Q = A.householderQr().householderQ();
// A = Q * Vec(2.2424567,2.2424566,7.454353).asDiagonal() * Q.transpose();
SelfAdjointEigenSolver<Mat> eig(A);
BENCH(t, tries, rep, eig.compute(A));
std::cout << "Eigen iterative: " << t.best() << "s\n";
BENCH(t, tries, rep, eig.computeDirect(A));
std::cout << "Eigen direct : " << t.best() << "s\n";
Mat evecs;
Vec evals;
BENCH(t, tries, rep, eigen33(A,evecs,evals));
std::cout << "Direct: " << t.best() << "s\n\n";
// std::cerr << "Eigenvalue/eigenvector diffs:\n";
// std::cerr << (evals - eig.eigenvalues()).transpose() << "\n";
// for(int k=0;k<3;++k)
// if(evecs.col(k).dot(eig.eigenvectors().col(k))<0)
// evecs.col(k) = -evecs.col(k);
// std::cerr << evecs - eig.eigenvectors() << "\n\n";
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/sparse_randomsetter.cpp | .cpp | 3,358 | 126 |
#define NOGMM
#define NOMTL
#include <map>
#include <ext/hash_map>
#include <google/dense_hash_map>
#include <google/sparse_hash_map>
#ifndef SIZE
#define SIZE 10000
#endif
#ifndef DENSITY
#define DENSITY 0.01
#endif
#ifndef REPEAT
#define REPEAT 1
#endif
#include "BenchSparseUtil.h"
#ifndef MINDENSITY
#define MINDENSITY 0.0004
#endif
#ifndef NBTRIES
#define NBTRIES 10
#endif
#define BENCH(X) \
timer.reset(); \
for (int _j=0; _j<NBTRIES; ++_j) { \
timer.start(); \
for (int _k=0; _k<REPEAT; ++_k) { \
X \
} timer.stop(); }
static double rtime;
static double nentries;
template<typename SetterType>
void dostuff(const char* name, EigenSparseMatrix& sm1)
{
int rows = sm1.rows();
int cols = sm1.cols();
sm1.setZero();
BenchTimer t;
SetterType* set1 = new SetterType(sm1);
t.reset(); t.start();
for (int k=0; k<nentries; ++k)
(*set1)(internal::random<int>(0,rows-1),internal::random<int>(0,cols-1)) += 1;
t.stop();
std::cout << "std::map => \t" << t.value()-rtime
<< " nnz=" << set1->nonZeros() << std::flush;
// getchar();
t.reset(); t.start(); delete set1; t.stop();
std::cout << " back: \t" << t.value() << "\n";
}
int main(int argc, char *argv[])
{
int rows = SIZE;
int cols = SIZE;
float density = DENSITY;
EigenSparseMatrix sm1(rows,cols), sm2(rows,cols);
nentries = rows*cols*density;
std::cout << "n = " << nentries << "\n";
int dummy;
BenchTimer t;
t.reset(); t.start();
for (int k=0; k<nentries; ++k)
dummy = internal::random<int>(0,rows-1) + internal::random<int>(0,cols-1);
t.stop();
rtime = t.value();
std::cout << "rtime = " << rtime << " (" << dummy << ")\n\n";
const int Bits = 6;
for (;;)
{
dostuff<RandomSetter<EigenSparseMatrix,StdMapTraits,Bits> >("std::map ", sm1);
dostuff<RandomSetter<EigenSparseMatrix,GnuHashMapTraits,Bits> >("gnu::hash_map", sm1);
dostuff<RandomSetter<EigenSparseMatrix,GoogleDenseHashMapTraits,Bits> >("google::dense", sm1);
dostuff<RandomSetter<EigenSparseMatrix,GoogleSparseHashMapTraits,Bits> >("google::sparse", sm1);
// {
// RandomSetter<EigenSparseMatrix,GnuHashMapTraits,Bits> set1(sm1);
// t.reset(); t.start();
// for (int k=0; k<n; ++k)
// set1(internal::random<int>(0,rows-1),internal::random<int>(0,cols-1)) += 1;
// t.stop();
// std::cout << "gnu::hash_map => \t" << t.value()-rtime
// << " nnz=" << set1.nonZeros() << "\n";getchar();
// }
// {
// RandomSetter<EigenSparseMatrix,GoogleDenseHashMapTraits,Bits> set1(sm1);
// t.reset(); t.start();
// for (int k=0; k<n; ++k)
// set1(internal::random<int>(0,rows-1),internal::random<int>(0,cols-1)) += 1;
// t.stop();
// std::cout << "google::dense => \t" << t.value()-rtime
// << " nnz=" << set1.nonZeros() << "\n";getchar();
// }
// {
// RandomSetter<EigenSparseMatrix,GoogleSparseHashMapTraits,Bits> set1(sm1);
// t.reset(); t.start();
// for (int k=0; k<n; ++k)
// set1(internal::random<int>(0,rows-1),internal::random<int>(0,cols-1)) += 1;
// t.stop();
// std::cout << "google::sparse => \t" << t.value()-rtime
// << " nnz=" << set1.nonZeros() << "\n";getchar();
// }
std::cout << "\n\n";
}
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/sparse_dense_product.cpp | .cpp | 5,101 | 188 |
//g++ -O3 -g0 -DNDEBUG sparse_product.cpp -I.. -I/home/gael/Coding/LinearAlgebra/mtl4/ -DDENSITY=0.005 -DSIZE=10000 && ./a.out
//g++ -O3 -g0 -DNDEBUG sparse_product.cpp -I.. -I/home/gael/Coding/LinearAlgebra/mtl4/ -DDENSITY=0.05 -DSIZE=2000 && ./a.out
// -DNOGMM -DNOMTL -DCSPARSE
// -I /home/gael/Coding/LinearAlgebra/CSparse/Include/ /home/gael/Coding/LinearAlgebra/CSparse/Lib/libcsparse.a
#ifndef SIZE
#define SIZE 650000
#endif
#ifndef DENSITY
#define DENSITY 0.01
#endif
#ifndef REPEAT
#define REPEAT 1
#endif
#include "BenchSparseUtil.h"
#ifndef MINDENSITY
#define MINDENSITY 0.0004
#endif
#ifndef NBTRIES
#define NBTRIES 10
#endif
#define BENCH(X) \
timer.reset(); \
for (int _j=0; _j<NBTRIES; ++_j) { \
timer.start(); \
for (int _k=0; _k<REPEAT; ++_k) { \
X \
} timer.stop(); }
#ifdef CSPARSE
cs* cs_sorted_multiply(const cs* a, const cs* b)
{
cs* A = cs_transpose (a, 1) ;
cs* B = cs_transpose (b, 1) ;
cs* D = cs_multiply (B,A) ; /* D = B'*A' */
cs_spfree (A) ;
cs_spfree (B) ;
cs_dropzeros (D) ; /* drop zeros from D */
cs* C = cs_transpose (D, 1) ; /* C = D', so that C is sorted */
cs_spfree (D) ;
return C;
}
#endif
int main(int argc, char *argv[])
{
int rows = SIZE;
int cols = SIZE;
float density = DENSITY;
EigenSparseMatrix sm1(rows,cols);
DenseVector v1(cols), v2(cols);
v1.setRandom();
BenchTimer timer;
for (float density = DENSITY; density>=MINDENSITY; density*=0.5)
{
//fillMatrix(density, rows, cols, sm1);
fillMatrix2(7, rows, cols, sm1);
// dense matrices
#ifdef DENSEMATRIX
{
std::cout << "Eigen Dense\t" << density*100 << "%\n";
DenseMatrix m1(rows,cols);
eiToDense(sm1, m1);
timer.reset();
timer.start();
for (int k=0; k<REPEAT; ++k)
v2 = m1 * v1;
timer.stop();
std::cout << " a * v:\t" << timer.best() << " " << double(REPEAT)/timer.best() << " * / sec " << endl;
timer.reset();
timer.start();
for (int k=0; k<REPEAT; ++k)
v2 = m1.transpose() * v1;
timer.stop();
std::cout << " a' * v:\t" << timer.best() << endl;
}
#endif
// eigen sparse matrices
{
std::cout << "Eigen sparse\t" << sm1.nonZeros()/float(sm1.rows()*sm1.cols())*100 << "%\n";
BENCH(asm("#myc"); v2 = sm1 * v1; asm("#myd");)
std::cout << " a * v:\t" << timer.best()/REPEAT << " " << double(REPEAT)/timer.best(REAL_TIMER) << " * / sec " << endl;
BENCH( { asm("#mya"); v2 = sm1.transpose() * v1; asm("#myb"); })
std::cout << " a' * v:\t" << timer.best()/REPEAT << endl;
}
// {
// DynamicSparseMatrix<Scalar> m1(sm1);
// std::cout << "Eigen dyn-sparse\t" << m1.nonZeros()/float(m1.rows()*m1.cols())*100 << "%\n";
//
// BENCH(for (int k=0; k<REPEAT; ++k) v2 = m1 * v1;)
// std::cout << " a * v:\t" << timer.value() << endl;
//
// BENCH(for (int k=0; k<REPEAT; ++k) v2 = m1.transpose() * v1;)
// std::cout << " a' * v:\t" << timer.value() << endl;
// }
// GMM++
#ifndef NOGMM
{
std::cout << "GMM++ sparse\t" << density*100 << "%\n";
//GmmDynSparse gmmT3(rows,cols);
GmmSparse m1(rows,cols);
eiToGmm(sm1, m1);
std::vector<Scalar> gmmV1(cols), gmmV2(cols);
Map<Matrix<Scalar,Dynamic,1> >(&gmmV1[0], cols) = v1;
Map<Matrix<Scalar,Dynamic,1> >(&gmmV2[0], cols) = v2;
BENCH( asm("#myx"); gmm::mult(m1, gmmV1, gmmV2); asm("#myy"); )
std::cout << " a * v:\t" << timer.value() << endl;
BENCH( gmm::mult(gmm::transposed(m1), gmmV1, gmmV2); )
std::cout << " a' * v:\t" << timer.value() << endl;
}
#endif
#ifndef NOUBLAS
{
std::cout << "ublas sparse\t" << density*100 << "%\n";
UBlasSparse m1(rows,cols);
eiToUblas(sm1, m1);
boost::numeric::ublas::vector<Scalar> uv1, uv2;
eiToUblasVec(v1,uv1);
eiToUblasVec(v2,uv2);
// std::vector<Scalar> gmmV1(cols), gmmV2(cols);
// Map<Matrix<Scalar,Dynamic,1> >(&gmmV1[0], cols) = v1;
// Map<Matrix<Scalar,Dynamic,1> >(&gmmV2[0], cols) = v2;
BENCH( uv2 = boost::numeric::ublas::prod(m1, uv1); )
std::cout << " a * v:\t" << timer.value() << endl;
// BENCH( boost::ublas::prod(gmm::transposed(m1), gmmV1, gmmV2); )
// std::cout << " a' * v:\t" << timer.value() << endl;
}
#endif
// MTL4
#ifndef NOMTL
{
std::cout << "MTL4\t" << density*100 << "%\n";
MtlSparse m1(rows,cols);
eiToMtl(sm1, m1);
mtl::dense_vector<Scalar> mtlV1(cols, 1.0);
mtl::dense_vector<Scalar> mtlV2(cols, 1.0);
timer.reset();
timer.start();
for (int k=0; k<REPEAT; ++k)
mtlV2 = m1 * mtlV1;
timer.stop();
std::cout << " a * v:\t" << timer.value() << endl;
timer.reset();
timer.start();
for (int k=0; k<REPEAT; ++k)
mtlV2 = trans(m1) * mtlV1;
timer.stop();
std::cout << " a' * v:\t" << timer.value() << endl;
}
#endif
std::cout << "\n\n";
}
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/benchFFT.cpp | .cpp | 2,806 | 116 | // This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2009 Mark Borgerding mark a borgerding net
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
#include <iostream>
#include <bench/BenchUtil.h>
#include <complex>
#include <vector>
#include <Eigen/Core>
#include <unsupported/Eigen/FFT>
using namespace Eigen;
using namespace std;
template <typename T>
string nameof();
template <> string nameof<float>() {return "float";}
template <> string nameof<double>() {return "double";}
template <> string nameof<long double>() {return "long double";}
#ifndef TYPE
#define TYPE float
#endif
#ifndef NFFT
#define NFFT 1024
#endif
#ifndef NDATA
#define NDATA 1000000
#endif
using namespace Eigen;
template <typename T>
void bench(int nfft,bool fwd,bool unscaled=false, bool halfspec=false)
{
typedef typename NumTraits<T>::Real Scalar;
typedef typename std::complex<Scalar> Complex;
int nits = NDATA/nfft;
vector<T> inbuf(nfft);
vector<Complex > outbuf(nfft);
FFT< Scalar > fft;
if (unscaled) {
fft.SetFlag(fft.Unscaled);
cout << "unscaled ";
}
if (halfspec) {
fft.SetFlag(fft.HalfSpectrum);
cout << "halfspec ";
}
std::fill(inbuf.begin(),inbuf.end(),0);
fft.fwd( outbuf , inbuf);
BenchTimer timer;
timer.reset();
for (int k=0;k<8;++k) {
timer.start();
if (fwd)
for(int i = 0; i < nits; i++)
fft.fwd( outbuf , inbuf);
else
for(int i = 0; i < nits; i++)
fft.inv(inbuf,outbuf);
timer.stop();
}
cout << nameof<Scalar>() << " ";
double mflops = 5.*nfft*log2((double)nfft) / (1e6 * timer.value() / (double)nits );
if ( NumTraits<T>::IsComplex ) {
cout << "complex";
}else{
cout << "real ";
mflops /= 2;
}
if (fwd)
cout << " fwd";
else
cout << " inv";
cout << " NFFT=" << nfft << " " << (double(1e-6*nfft*nits)/timer.value()) << " MS/s " << mflops << "MFLOPS\n";
}
int main(int argc,char ** argv)
{
bench<complex<float> >(NFFT,true);
bench<complex<float> >(NFFT,false);
bench<float>(NFFT,true);
bench<float>(NFFT,false);
bench<float>(NFFT,false,true);
bench<float>(NFFT,false,true,true);
bench<complex<double> >(NFFT,true);
bench<complex<double> >(NFFT,false);
bench<double>(NFFT,true);
bench<double>(NFFT,false);
bench<complex<long double> >(NFFT,true);
bench<complex<long double> >(NFFT,false);
bench<long double>(NFFT,true);
bench<long double>(NFFT,false);
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/sparse_transpose.cpp | .cpp | 2,347 | 105 |
//g++ -O3 -g0 -DNDEBUG sparse_transpose.cpp -I.. -I/home/gael/Coding/LinearAlgebra/mtl4/ -DDENSITY=0.005 -DSIZE=10000 && ./a.out
// -DNOGMM -DNOMTL
// -DCSPARSE -I /home/gael/Coding/LinearAlgebra/CSparse/Include/ /home/gael/Coding/LinearAlgebra/CSparse/Lib/libcsparse.a
#ifndef SIZE
#define SIZE 10000
#endif
#ifndef DENSITY
#define DENSITY 0.01
#endif
#ifndef REPEAT
#define REPEAT 1
#endif
#include "BenchSparseUtil.h"
#ifndef MINDENSITY
#define MINDENSITY 0.0004
#endif
#ifndef NBTRIES
#define NBTRIES 10
#endif
#define BENCH(X) \
timer.reset(); \
for (int _j=0; _j<NBTRIES; ++_j) { \
timer.start(); \
for (int _k=0; _k<REPEAT; ++_k) { \
X \
} timer.stop(); }
int main(int argc, char *argv[])
{
int rows = SIZE;
int cols = SIZE;
float density = DENSITY;
EigenSparseMatrix sm1(rows,cols), sm3(rows,cols);
BenchTimer timer;
for (float density = DENSITY; density>=MINDENSITY; density*=0.5)
{
fillMatrix(density, rows, cols, sm1);
// dense matrices
#ifdef DENSEMATRIX
{
DenseMatrix m1(rows,cols), m3(rows,cols);
eiToDense(sm1, m1);
BENCH(for (int k=0; k<REPEAT; ++k) m3 = m1.transpose();)
std::cout << " Eigen dense:\t" << timer.value() << endl;
}
#endif
std::cout << "Non zeros: " << sm1.nonZeros()/float(sm1.rows()*sm1.cols())*100 << "%\n";
// eigen sparse matrices
{
BENCH(for (int k=0; k<REPEAT; ++k) sm3 = sm1.transpose();)
std::cout << " Eigen:\t" << timer.value() << endl;
}
// CSparse
#ifdef CSPARSE
{
cs *m1, *m3;
eiToCSparse(sm1, m1);
BENCH(for (int k=0; k<REPEAT; ++k) { m3 = cs_transpose(m1,1); cs_spfree(m3);})
std::cout << " CSparse:\t" << timer.value() << endl;
}
#endif
// GMM++
#ifndef NOGMM
{
GmmDynSparse gmmT3(rows,cols);
GmmSparse m1(rows,cols), m3(rows,cols);
eiToGmm(sm1, m1);
BENCH(for (int k=0; k<REPEAT; ++k) gmm::copy(gmm::transposed(m1),m3);)
std::cout << " GMM:\t\t" << timer.value() << endl;
}
#endif
// MTL4
#ifndef NOMTL
{
MtlSparse m1(rows,cols), m3(rows,cols);
eiToMtl(sm1, m1);
BENCH(for (int k=0; k<REPEAT; ++k) m3 = trans(m1);)
std::cout << " MTL4:\t\t" << timer.value() << endl;
}
#endif
std::cout << "\n\n";
}
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/sparse_trisolver.cpp | .cpp | 6,114 | 221 |
//g++ -O3 -g0 -DNDEBUG sparse_product.cpp -I.. -I/home/gael/Coding/LinearAlgebra/mtl4/ -DDENSITY=0.005 -DSIZE=10000 && ./a.out
//g++ -O3 -g0 -DNDEBUG sparse_product.cpp -I.. -I/home/gael/Coding/LinearAlgebra/mtl4/ -DDENSITY=0.05 -DSIZE=2000 && ./a.out
// -DNOGMM -DNOMTL
// -I /home/gael/Coding/LinearAlgebra/CSparse/Include/ /home/gael/Coding/LinearAlgebra/CSparse/Lib/libcsparse.a
#ifndef SIZE
#define SIZE 10000
#endif
#ifndef DENSITY
#define DENSITY 0.01
#endif
#ifndef REPEAT
#define REPEAT 1
#endif
#include "BenchSparseUtil.h"
#ifndef MINDENSITY
#define MINDENSITY 0.0004
#endif
#ifndef NBTRIES
#define NBTRIES 10
#endif
#define BENCH(X) \
timer.reset(); \
for (int _j=0; _j<NBTRIES; ++_j) { \
timer.start(); \
for (int _k=0; _k<REPEAT; ++_k) { \
X \
} timer.stop(); }
typedef SparseMatrix<Scalar,UpperTriangular> EigenSparseTriMatrix;
typedef SparseMatrix<Scalar,RowMajorBit|UpperTriangular> EigenSparseTriMatrixRow;
void fillMatrix(float density, int rows, int cols, EigenSparseTriMatrix& dst)
{
dst.startFill(rows*cols*density);
for(int j = 0; j < cols; j++)
{
for(int i = 0; i < j; i++)
{
Scalar v = (internal::random<float>(0,1) < density) ? internal::random<Scalar>() : 0;
if (v!=0)
dst.fill(i,j) = v;
}
dst.fill(j,j) = internal::random<Scalar>();
}
dst.endFill();
}
int main(int argc, char *argv[])
{
int rows = SIZE;
int cols = SIZE;
float density = DENSITY;
BenchTimer timer;
#if 1
EigenSparseTriMatrix sm1(rows,cols);
typedef Matrix<Scalar,Dynamic,1> DenseVector;
DenseVector b = DenseVector::Random(cols);
DenseVector x = DenseVector::Random(cols);
bool densedone = false;
for (float density = DENSITY; density>=MINDENSITY; density*=0.5)
{
EigenSparseTriMatrix sm1(rows, cols);
fillMatrix(density, rows, cols, sm1);
// dense matrices
#ifdef DENSEMATRIX
if (!densedone)
{
densedone = true;
std::cout << "Eigen Dense\t" << density*100 << "%\n";
DenseMatrix m1(rows,cols);
Matrix<Scalar,Dynamic,Dynamic,Dynamic,Dynamic,RowMajorBit> m2(rows,cols);
eiToDense(sm1, m1);
m2 = m1;
BENCH(x = m1.marked<UpperTriangular>().solveTriangular(b);)
std::cout << " colmajor^-1 * b:\t" << timer.value() << endl;
// std::cerr << x.transpose() << "\n";
BENCH(x = m2.marked<UpperTriangular>().solveTriangular(b);)
std::cout << " rowmajor^-1 * b:\t" << timer.value() << endl;
// std::cerr << x.transpose() << "\n";
}
#endif
// eigen sparse matrices
{
std::cout << "Eigen sparse\t" << density*100 << "%\n";
EigenSparseTriMatrixRow sm2 = sm1;
BENCH(x = sm1.solveTriangular(b);)
std::cout << " colmajor^-1 * b:\t" << timer.value() << endl;
// std::cerr << x.transpose() << "\n";
BENCH(x = sm2.solveTriangular(b);)
std::cout << " rowmajor^-1 * b:\t" << timer.value() << endl;
// std::cerr << x.transpose() << "\n";
// x = b;
// BENCH(sm1.inverseProductInPlace(x);)
// std::cout << " colmajor^-1 * b:\t" << timer.value() << " (inplace)" << endl;
// std::cerr << x.transpose() << "\n";
//
// x = b;
// BENCH(sm2.inverseProductInPlace(x);)
// std::cout << " rowmajor^-1 * b:\t" << timer.value() << " (inplace)" << endl;
// std::cerr << x.transpose() << "\n";
}
// CSparse
#ifdef CSPARSE
{
std::cout << "CSparse \t" << density*100 << "%\n";
cs *m1;
eiToCSparse(sm1, m1);
BENCH(x = b; if (!cs_lsolve (m1, x.data())){std::cerr << "cs_lsolve failed\n"; break;}; )
std::cout << " colmajor^-1 * b:\t" << timer.value() << endl;
}
#endif
// GMM++
#ifndef NOGMM
{
std::cout << "GMM++ sparse\t" << density*100 << "%\n";
GmmSparse m1(rows,cols);
gmm::csr_matrix<Scalar> m2;
eiToGmm(sm1, m1);
gmm::copy(m1,m2);
std::vector<Scalar> gmmX(cols), gmmB(cols);
Map<Matrix<Scalar,Dynamic,1> >(&gmmX[0], cols) = x;
Map<Matrix<Scalar,Dynamic,1> >(&gmmB[0], cols) = b;
gmmX = gmmB;
BENCH(gmm::upper_tri_solve(m1, gmmX, false);)
std::cout << " colmajor^-1 * b:\t" << timer.value() << endl;
// std::cerr << Map<Matrix<Scalar,Dynamic,1> >(&gmmX[0], cols).transpose() << "\n";
gmmX = gmmB;
BENCH(gmm::upper_tri_solve(m2, gmmX, false);)
timer.stop();
std::cout << " rowmajor^-1 * b:\t" << timer.value() << endl;
// std::cerr << Map<Matrix<Scalar,Dynamic,1> >(&gmmX[0], cols).transpose() << "\n";
}
#endif
// MTL4
#ifndef NOMTL
{
std::cout << "MTL4\t" << density*100 << "%\n";
MtlSparse m1(rows,cols);
MtlSparseRowMajor m2(rows,cols);
eiToMtl(sm1, m1);
m2 = m1;
mtl::dense_vector<Scalar> x(rows, 1.0);
mtl::dense_vector<Scalar> b(rows, 1.0);
BENCH(x = mtl::upper_trisolve(m1,b);)
std::cout << " colmajor^-1 * b:\t" << timer.value() << endl;
// std::cerr << x << "\n";
BENCH(x = mtl::upper_trisolve(m2,b);)
std::cout << " rowmajor^-1 * b:\t" << timer.value() << endl;
// std::cerr << x << "\n";
}
#endif
std::cout << "\n\n";
}
#endif
#if 0
// bench small matrices (in-place versus return bye value)
{
timer.reset();
for (int _j=0; _j<10; ++_j) {
Matrix4f m = Matrix4f::Random();
Vector4f b = Vector4f::Random();
Vector4f x = Vector4f::Random();
timer.start();
for (int _k=0; _k<1000000; ++_k) {
b = m.inverseProduct(b);
}
timer.stop();
}
std::cout << "4x4 :\t" << timer.value() << endl;
}
{
timer.reset();
for (int _j=0; _j<10; ++_j) {
Matrix4f m = Matrix4f::Random();
Vector4f b = Vector4f::Random();
Vector4f x = Vector4f::Random();
timer.start();
for (int _k=0; _k<1000000; ++_k) {
m.inverseProductInPlace(x);
}
timer.stop();
}
std::cout << "4x4 IP :\t" << timer.value() << endl;
}
#endif
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/benchmark-blocking-sizes.cpp | .cpp | 22,259 | 678 | // This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2015 Benoit Jacob <benoitjacob@google.com>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
#include <iostream>
#include <cstdint>
#include <cstdlib>
#include <vector>
#include <fstream>
#include <memory>
#include <cstdio>
bool eigen_use_specific_block_size;
int eigen_block_size_k, eigen_block_size_m, eigen_block_size_n;
#define EIGEN_TEST_SPECIFIC_BLOCKING_SIZES eigen_use_specific_block_size
#define EIGEN_TEST_SPECIFIC_BLOCKING_SIZE_K eigen_block_size_k
#define EIGEN_TEST_SPECIFIC_BLOCKING_SIZE_M eigen_block_size_m
#define EIGEN_TEST_SPECIFIC_BLOCKING_SIZE_N eigen_block_size_n
#include <Eigen/Core>
#include <bench/BenchTimer.h>
using namespace Eigen;
using namespace std;
static BenchTimer timer;
// how many times we repeat each measurement.
// measurements are randomly shuffled - we're not doing
// all N identical measurements in a row.
const int measurement_repetitions = 3;
// Timings below this value are too short to be accurate,
// we'll repeat measurements with more iterations until
// we get a timing above that threshold.
const float min_accurate_time = 1e-2f;
// See --min-working-set-size command line parameter.
size_t min_working_set_size = 0;
float max_clock_speed = 0.0f;
// range of sizes that we will benchmark (in all 3 K,M,N dimensions)
const size_t maxsize = 2048;
const size_t minsize = 16;
typedef MatrixXf MatrixType;
typedef MatrixType::Scalar Scalar;
typedef internal::packet_traits<Scalar>::type Packet;
static_assert((maxsize & (maxsize - 1)) == 0, "maxsize must be a power of two");
static_assert((minsize & (minsize - 1)) == 0, "minsize must be a power of two");
static_assert(maxsize > minsize, "maxsize must be larger than minsize");
static_assert(maxsize < (minsize << 16), "maxsize must be less than (minsize<<16)");
// just a helper to store a triple of K,M,N sizes for matrix product
struct size_triple_t
{
size_t k, m, n;
size_triple_t() : k(0), m(0), n(0) {}
size_triple_t(size_t _k, size_t _m, size_t _n) : k(_k), m(_m), n(_n) {}
size_triple_t(const size_triple_t& o) : k(o.k), m(o.m), n(o.n) {}
size_triple_t(uint16_t compact)
{
k = 1 << ((compact & 0xf00) >> 8);
m = 1 << ((compact & 0x0f0) >> 4);
n = 1 << ((compact & 0x00f) >> 0);
}
};
uint8_t log2_pot(size_t x) {
size_t l = 0;
while (x >>= 1) l++;
return l;
}
// Convert between size tripes and a compact form fitting in 12 bits
// where each size, which must be a POT, is encoded as its log2, on 4 bits
// so the largest representable size is 2^15 == 32k ... big enough.
uint16_t compact_size_triple(size_t k, size_t m, size_t n)
{
return (log2_pot(k) << 8) | (log2_pot(m) << 4) | log2_pot(n);
}
uint16_t compact_size_triple(const size_triple_t& t)
{
return compact_size_triple(t.k, t.m, t.n);
}
// A single benchmark. Initially only contains benchmark params.
// Then call run(), which stores the result in the gflops field.
struct benchmark_t
{
uint16_t compact_product_size;
uint16_t compact_block_size;
bool use_default_block_size;
float gflops;
benchmark_t()
: compact_product_size(0)
, compact_block_size(0)
, use_default_block_size(false)
, gflops(0)
{
}
benchmark_t(size_t pk, size_t pm, size_t pn,
size_t bk, size_t bm, size_t bn)
: compact_product_size(compact_size_triple(pk, pm, pn))
, compact_block_size(compact_size_triple(bk, bm, bn))
, use_default_block_size(false)
, gflops(0)
{}
benchmark_t(size_t pk, size_t pm, size_t pn)
: compact_product_size(compact_size_triple(pk, pm, pn))
, compact_block_size(0)
, use_default_block_size(true)
, gflops(0)
{}
void run();
};
ostream& operator<<(ostream& s, const benchmark_t& b)
{
s << hex << b.compact_product_size << dec;
if (b.use_default_block_size) {
size_triple_t t(b.compact_product_size);
Index k = t.k, m = t.m, n = t.n;
internal::computeProductBlockingSizes<Scalar, Scalar>(k, m, n);
s << " default(" << k << ", " << m << ", " << n << ")";
} else {
s << " " << hex << b.compact_block_size << dec;
}
s << " " << b.gflops;
return s;
}
// We sort first by increasing benchmark parameters,
// then by decreasing performance.
bool operator<(const benchmark_t& b1, const benchmark_t& b2)
{
return b1.compact_product_size < b2.compact_product_size ||
(b1.compact_product_size == b2.compact_product_size && (
(b1.compact_block_size < b2.compact_block_size || (
b1.compact_block_size == b2.compact_block_size &&
b1.gflops > b2.gflops))));
}
void benchmark_t::run()
{
size_triple_t productsizes(compact_product_size);
if (use_default_block_size) {
eigen_use_specific_block_size = false;
} else {
// feed eigen with our custom blocking params
eigen_use_specific_block_size = true;
size_triple_t blocksizes(compact_block_size);
eigen_block_size_k = blocksizes.k;
eigen_block_size_m = blocksizes.m;
eigen_block_size_n = blocksizes.n;
}
// set up the matrix pool
const size_t combined_three_matrices_sizes =
sizeof(Scalar) *
(productsizes.k * productsizes.m +
productsizes.k * productsizes.n +
productsizes.m * productsizes.n);
// 64 M is large enough that nobody has a cache bigger than that,
// while still being small enough that everybody has this much RAM,
// so conveniently we don't need to special-case platforms here.
const size_t unlikely_large_cache_size = 64 << 20;
const size_t working_set_size =
min_working_set_size ? min_working_set_size : unlikely_large_cache_size;
const size_t matrix_pool_size =
1 + working_set_size / combined_three_matrices_sizes;
MatrixType *lhs = new MatrixType[matrix_pool_size];
MatrixType *rhs = new MatrixType[matrix_pool_size];
MatrixType *dst = new MatrixType[matrix_pool_size];
for (size_t i = 0; i < matrix_pool_size; i++) {
lhs[i] = MatrixType::Zero(productsizes.m, productsizes.k);
rhs[i] = MatrixType::Zero(productsizes.k, productsizes.n);
dst[i] = MatrixType::Zero(productsizes.m, productsizes.n);
}
// main benchmark loop
int iters_at_a_time = 1;
float time_per_iter = 0.0f;
size_t matrix_index = 0;
while (true) {
double starttime = timer.getCpuTime();
for (int i = 0; i < iters_at_a_time; i++) {
dst[matrix_index].noalias() = lhs[matrix_index] * rhs[matrix_index];
matrix_index++;
if (matrix_index == matrix_pool_size) {
matrix_index = 0;
}
}
double endtime = timer.getCpuTime();
const float timing = float(endtime - starttime);
if (timing >= min_accurate_time) {
time_per_iter = timing / iters_at_a_time;
break;
}
iters_at_a_time *= 2;
}
delete[] lhs;
delete[] rhs;
delete[] dst;
gflops = 2e-9 * productsizes.k * productsizes.m * productsizes.n / time_per_iter;
}
void print_cpuinfo()
{
#ifdef __linux__
cout << "contents of /proc/cpuinfo:" << endl;
string line;
ifstream cpuinfo("/proc/cpuinfo");
if (cpuinfo.is_open()) {
while (getline(cpuinfo, line)) {
cout << line << endl;
}
cpuinfo.close();
}
cout << endl;
#elif defined __APPLE__
cout << "output of sysctl hw:" << endl;
system("sysctl hw");
cout << endl;
#endif
}
template <typename T>
string type_name()
{
return "unknown";
}
template<>
string type_name<float>()
{
return "float";
}
template<>
string type_name<double>()
{
return "double";
}
struct action_t
{
virtual const char* invokation_name() const { abort(); return nullptr; }
virtual void run() const { abort(); }
virtual ~action_t() {}
};
void show_usage_and_exit(int /*argc*/, char* argv[],
const vector<unique_ptr<action_t>>& available_actions)
{
cerr << "usage: " << argv[0] << " <action> [options...]" << endl << endl;
cerr << "available actions:" << endl << endl;
for (auto it = available_actions.begin(); it != available_actions.end(); ++it) {
cerr << " " << (*it)->invokation_name() << endl;
}
cerr << endl;
cerr << "options:" << endl << endl;
cerr << " --min-working-set-size=N:" << endl;
cerr << " Set the minimum working set size to N bytes." << endl;
cerr << " This is rounded up as needed to a multiple of matrix size." << endl;
cerr << " A larger working set lowers the chance of a warm cache." << endl;
cerr << " The default value 0 means use a large enough working" << endl;
cerr << " set to likely outsize caches." << endl;
cerr << " A value of 1 (that is, 1 byte) would mean don't do anything to" << endl;
cerr << " avoid warm caches." << endl;
exit(1);
}
float measure_clock_speed()
{
cerr << "Measuring clock speed... \r" << flush;
vector<float> all_gflops;
for (int i = 0; i < 8; i++) {
benchmark_t b(1024, 1024, 1024);
b.run();
all_gflops.push_back(b.gflops);
}
sort(all_gflops.begin(), all_gflops.end());
float stable_estimate = all_gflops[2] + all_gflops[3] + all_gflops[4] + all_gflops[5];
// multiply by an arbitrary constant to discourage trying doing anything with the
// returned values besides just comparing them with each other.
float result = stable_estimate * 123.456f;
return result;
}
struct human_duration_t
{
int seconds;
human_duration_t(int s) : seconds(s) {}
};
ostream& operator<<(ostream& s, const human_duration_t& d)
{
int remainder = d.seconds;
if (remainder > 3600) {
int hours = remainder / 3600;
s << hours << " h ";
remainder -= hours * 3600;
}
if (remainder > 60) {
int minutes = remainder / 60;
s << minutes << " min ";
remainder -= minutes * 60;
}
if (d.seconds < 600) {
s << remainder << " s";
}
return s;
}
const char session_filename[] = "/data/local/tmp/benchmark-blocking-sizes-session.data";
void serialize_benchmarks(const char* filename, const vector<benchmark_t>& benchmarks, size_t first_benchmark_to_run)
{
FILE* file = fopen(filename, "w");
if (!file) {
cerr << "Could not open file " << filename << " for writing." << endl;
cerr << "Do you have write permissions on the current working directory?" << endl;
exit(1);
}
size_t benchmarks_vector_size = benchmarks.size();
fwrite(&max_clock_speed, sizeof(max_clock_speed), 1, file);
fwrite(&benchmarks_vector_size, sizeof(benchmarks_vector_size), 1, file);
fwrite(&first_benchmark_to_run, sizeof(first_benchmark_to_run), 1, file);
fwrite(benchmarks.data(), sizeof(benchmark_t), benchmarks.size(), file);
fclose(file);
}
bool deserialize_benchmarks(const char* filename, vector<benchmark_t>& benchmarks, size_t& first_benchmark_to_run)
{
FILE* file = fopen(filename, "r");
if (!file) {
return false;
}
if (1 != fread(&max_clock_speed, sizeof(max_clock_speed), 1, file)) {
return false;
}
size_t benchmarks_vector_size = 0;
if (1 != fread(&benchmarks_vector_size, sizeof(benchmarks_vector_size), 1, file)) {
return false;
}
if (1 != fread(&first_benchmark_to_run, sizeof(first_benchmark_to_run), 1, file)) {
return false;
}
benchmarks.resize(benchmarks_vector_size);
if (benchmarks.size() != fread(benchmarks.data(), sizeof(benchmark_t), benchmarks.size(), file)) {
return false;
}
unlink(filename);
return true;
}
void try_run_some_benchmarks(
vector<benchmark_t>& benchmarks,
double time_start,
size_t& first_benchmark_to_run)
{
if (first_benchmark_to_run == benchmarks.size()) {
return;
}
double time_last_progress_update = 0;
double time_last_clock_speed_measurement = 0;
double time_now = 0;
size_t benchmark_index = first_benchmark_to_run;
while (true) {
float ratio_done = float(benchmark_index) / benchmarks.size();
time_now = timer.getRealTime();
// We check clock speed every minute and at the end.
if (benchmark_index == benchmarks.size() ||
time_now > time_last_clock_speed_measurement + 60.0f)
{
time_last_clock_speed_measurement = time_now;
// Ensure that clock speed is as expected
float current_clock_speed = measure_clock_speed();
// The tolerance needs to be smaller than the relative difference between
// clock speeds that a device could operate under.
// It seems unlikely that a device would be throttling clock speeds by
// amounts smaller than 2%.
// With a value of 1%, I was getting within noise on a Sandy Bridge.
const float clock_speed_tolerance = 0.02f;
if (current_clock_speed > (1 + clock_speed_tolerance) * max_clock_speed) {
// Clock speed is now higher than we previously measured.
// Either our initial measurement was inaccurate, which won't happen
// too many times as we are keeping the best clock speed value and
// and allowing some tolerance; or something really weird happened,
// which invalidates all benchmark results collected so far.
// Either way, we better restart all over again now.
if (benchmark_index) {
cerr << "Restarting at " << 100.0f * ratio_done
<< " % because clock speed increased. " << endl;
}
max_clock_speed = current_clock_speed;
first_benchmark_to_run = 0;
return;
}
bool rerun_last_tests = false;
if (current_clock_speed < (1 - clock_speed_tolerance) * max_clock_speed) {
cerr << "Measurements completed so far: "
<< 100.0f * ratio_done
<< " % " << endl;
cerr << "Clock speed seems to be only "
<< current_clock_speed/max_clock_speed
<< " times what it used to be." << endl;
unsigned int seconds_to_sleep_if_lower_clock_speed = 1;
while (current_clock_speed < (1 - clock_speed_tolerance) * max_clock_speed) {
if (seconds_to_sleep_if_lower_clock_speed > 32) {
cerr << "Sleeping longer probably won't make a difference." << endl;
cerr << "Serializing benchmarks to " << session_filename << endl;
serialize_benchmarks(session_filename, benchmarks, first_benchmark_to_run);
cerr << "Now restart this benchmark, and it should pick up where we left." << endl;
exit(2);
}
rerun_last_tests = true;
cerr << "Sleeping "
<< seconds_to_sleep_if_lower_clock_speed
<< " s... \r" << endl;
sleep(seconds_to_sleep_if_lower_clock_speed);
current_clock_speed = measure_clock_speed();
seconds_to_sleep_if_lower_clock_speed *= 2;
}
}
if (rerun_last_tests) {
cerr << "Redoing the last "
<< 100.0f * float(benchmark_index - first_benchmark_to_run) / benchmarks.size()
<< " % because clock speed had been low. " << endl;
return;
}
// nothing wrong with the clock speed so far, so there won't be a need to rerun
// benchmarks run so far in case we later encounter a lower clock speed.
first_benchmark_to_run = benchmark_index;
}
if (benchmark_index == benchmarks.size()) {
// We're done!
first_benchmark_to_run = benchmarks.size();
// Erase progress info
cerr << " " << endl;
return;
}
// Display progress info on stderr
if (time_now > time_last_progress_update + 1.0f) {
time_last_progress_update = time_now;
cerr << "Measurements... " << 100.0f * ratio_done
<< " %, ETA "
<< human_duration_t(float(time_now - time_start) * (1.0f - ratio_done) / ratio_done)
<< " \r" << flush;
}
// This is where we actually run a benchmark!
benchmarks[benchmark_index].run();
benchmark_index++;
}
}
void run_benchmarks(vector<benchmark_t>& benchmarks)
{
size_t first_benchmark_to_run;
vector<benchmark_t> deserialized_benchmarks;
bool use_deserialized_benchmarks = false;
if (deserialize_benchmarks(session_filename, deserialized_benchmarks, first_benchmark_to_run)) {
cerr << "Found serialized session with "
<< 100.0f * first_benchmark_to_run / deserialized_benchmarks.size()
<< " % already done" << endl;
if (deserialized_benchmarks.size() == benchmarks.size() &&
first_benchmark_to_run > 0 &&
first_benchmark_to_run < benchmarks.size())
{
use_deserialized_benchmarks = true;
}
}
if (use_deserialized_benchmarks) {
benchmarks = deserialized_benchmarks;
} else {
// not using deserialized benchmarks, starting from scratch
first_benchmark_to_run = 0;
// Randomly shuffling benchmarks allows us to get accurate enough progress info,
// as now the cheap/expensive benchmarks are randomly mixed so they average out.
// It also means that if data is corrupted for some time span, the odds are that
// not all repetitions of a given benchmark will be corrupted.
random_shuffle(benchmarks.begin(), benchmarks.end());
}
for (int i = 0; i < 4; i++) {
max_clock_speed = max(max_clock_speed, measure_clock_speed());
}
double time_start = 0.0;
while (first_benchmark_to_run < benchmarks.size()) {
if (first_benchmark_to_run == 0) {
time_start = timer.getRealTime();
}
try_run_some_benchmarks(benchmarks,
time_start,
first_benchmark_to_run);
}
// Sort timings by increasing benchmark parameters, and decreasing gflops.
// The latter is very important. It means that we can ignore all but the first
// benchmark with given parameters.
sort(benchmarks.begin(), benchmarks.end());
// Collect best (i.e. now first) results for each parameter values.
vector<benchmark_t> best_benchmarks;
for (auto it = benchmarks.begin(); it != benchmarks.end(); ++it) {
if (best_benchmarks.empty() ||
best_benchmarks.back().compact_product_size != it->compact_product_size ||
best_benchmarks.back().compact_block_size != it->compact_block_size)
{
best_benchmarks.push_back(*it);
}
}
// keep and return only the best benchmarks
benchmarks = best_benchmarks;
}
struct measure_all_pot_sizes_action_t : action_t
{
virtual const char* invokation_name() const { return "all-pot-sizes"; }
virtual void run() const
{
vector<benchmark_t> benchmarks;
for (int repetition = 0; repetition < measurement_repetitions; repetition++) {
for (size_t ksize = minsize; ksize <= maxsize; ksize *= 2) {
for (size_t msize = minsize; msize <= maxsize; msize *= 2) {
for (size_t nsize = minsize; nsize <= maxsize; nsize *= 2) {
for (size_t kblock = minsize; kblock <= ksize; kblock *= 2) {
for (size_t mblock = minsize; mblock <= msize; mblock *= 2) {
for (size_t nblock = minsize; nblock <= nsize; nblock *= 2) {
benchmarks.emplace_back(ksize, msize, nsize, kblock, mblock, nblock);
}
}
}
}
}
}
}
run_benchmarks(benchmarks);
cout << "BEGIN MEASUREMENTS ALL POT SIZES" << endl;
for (auto it = benchmarks.begin(); it != benchmarks.end(); ++it) {
cout << *it << endl;
}
}
};
struct measure_default_sizes_action_t : action_t
{
virtual const char* invokation_name() const { return "default-sizes"; }
virtual void run() const
{
vector<benchmark_t> benchmarks;
for (int repetition = 0; repetition < measurement_repetitions; repetition++) {
for (size_t ksize = minsize; ksize <= maxsize; ksize *= 2) {
for (size_t msize = minsize; msize <= maxsize; msize *= 2) {
for (size_t nsize = minsize; nsize <= maxsize; nsize *= 2) {
benchmarks.emplace_back(ksize, msize, nsize);
}
}
}
}
run_benchmarks(benchmarks);
cout << "BEGIN MEASUREMENTS DEFAULT SIZES" << endl;
for (auto it = benchmarks.begin(); it != benchmarks.end(); ++it) {
cout << *it << endl;
}
}
};
int main(int argc, char* argv[])
{
double time_start = timer.getRealTime();
cout.precision(4);
cerr.precision(4);
vector<unique_ptr<action_t>> available_actions;
available_actions.emplace_back(new measure_all_pot_sizes_action_t);
available_actions.emplace_back(new measure_default_sizes_action_t);
auto action = available_actions.end();
if (argc <= 1) {
show_usage_and_exit(argc, argv, available_actions);
}
for (auto it = available_actions.begin(); it != available_actions.end(); ++it) {
if (!strcmp(argv[1], (*it)->invokation_name())) {
action = it;
break;
}
}
if (action == available_actions.end()) {
show_usage_and_exit(argc, argv, available_actions);
}
for (int i = 2; i < argc; i++) {
if (argv[i] == strstr(argv[i], "--min-working-set-size=")) {
const char* equals_sign = strchr(argv[i], '=');
min_working_set_size = strtoul(equals_sign+1, nullptr, 10);
} else {
cerr << "unrecognized option: " << argv[i] << endl << endl;
show_usage_and_exit(argc, argv, available_actions);
}
}
print_cpuinfo();
cout << "benchmark parameters:" << endl;
cout << "pointer size: " << 8*sizeof(void*) << " bits" << endl;
cout << "scalar type: " << type_name<Scalar>() << endl;
cout << "packet size: " << internal::packet_traits<MatrixType::Scalar>::size << endl;
cout << "minsize = " << minsize << endl;
cout << "maxsize = " << maxsize << endl;
cout << "measurement_repetitions = " << measurement_repetitions << endl;
cout << "min_accurate_time = " << min_accurate_time << endl;
cout << "min_working_set_size = " << min_working_set_size;
if (min_working_set_size == 0) {
cout << " (try to outsize caches)";
}
cout << endl << endl;
(*action)->run();
double time_end = timer.getRealTime();
cerr << "Finished in " << human_duration_t(time_end - time_start) << endl;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/geometry.cpp | .cpp | 3,307 | 127 |
#include <iostream>
#include <Eigen/Geometry>
#include <bench/BenchTimer.h>
using namespace std;
using namespace Eigen;
#ifndef SCALAR
#define SCALAR float
#endif
#ifndef SIZE
#define SIZE 8
#endif
typedef SCALAR Scalar;
typedef NumTraits<Scalar>::Real RealScalar;
typedef Matrix<RealScalar,Dynamic,Dynamic> A;
typedef Matrix</*Real*/Scalar,Dynamic,Dynamic> B;
typedef Matrix<Scalar,Dynamic,Dynamic> C;
typedef Matrix<RealScalar,Dynamic,Dynamic> M;
template<typename Transformation, typename Data>
EIGEN_DONT_INLINE void transform(const Transformation& t, Data& data)
{
EIGEN_ASM_COMMENT("begin");
data = t * data;
EIGEN_ASM_COMMENT("end");
}
template<typename Scalar, typename Data>
EIGEN_DONT_INLINE void transform(const Quaternion<Scalar>& t, Data& data)
{
EIGEN_ASM_COMMENT("begin quat");
for(int i=0;i<data.cols();++i)
data.col(i) = t * data.col(i);
EIGEN_ASM_COMMENT("end quat");
}
template<typename T> struct ToRotationMatrixWrapper
{
enum {Dim = T::Dim};
typedef typename T::Scalar Scalar;
ToRotationMatrixWrapper(const T& o) : object(o) {}
T object;
};
template<typename QType, typename Data>
EIGEN_DONT_INLINE void transform(const ToRotationMatrixWrapper<QType>& t, Data& data)
{
EIGEN_ASM_COMMENT("begin quat via mat");
data = t.object.toRotationMatrix() * data;
EIGEN_ASM_COMMENT("end quat via mat");
}
template<typename Scalar, int Dim, typename Data>
EIGEN_DONT_INLINE void transform(const Transform<Scalar,Dim,Projective>& t, Data& data)
{
data = (t * data.colwise().homogeneous()).template block<Dim,Data::ColsAtCompileTime>(0,0);
}
template<typename T> struct get_dim { enum { Dim = T::Dim }; };
template<typename S, int R, int C, int O, int MR, int MC>
struct get_dim<Matrix<S,R,C,O,MR,MC> > { enum { Dim = R }; };
template<typename Transformation, int N>
struct bench_impl
{
static EIGEN_DONT_INLINE void run(const Transformation& t)
{
Matrix<typename Transformation::Scalar,get_dim<Transformation>::Dim,N> data;
data.setRandom();
bench_impl<Transformation,N-1>::run(t);
BenchTimer timer;
BENCH(timer,10,100000,transform(t,data));
cout.width(9);
cout << timer.best() << " ";
}
};
template<typename Transformation>
struct bench_impl<Transformation,0>
{
static EIGEN_DONT_INLINE void run(const Transformation&) {}
};
template<typename Transformation>
EIGEN_DONT_INLINE void bench(const std::string& msg, const Transformation& t)
{
cout << msg << " ";
bench_impl<Transformation,SIZE>::run(t);
std::cout << "\n";
}
int main(int argc, char ** argv)
{
Matrix<Scalar,3,4> mat34; mat34.setRandom();
Transform<Scalar,3,Isometry> iso3(mat34);
Transform<Scalar,3,Affine> aff3(mat34);
Transform<Scalar,3,AffineCompact> caff3(mat34);
Transform<Scalar,3,Projective> proj3(mat34);
Quaternion<Scalar> quat;quat.setIdentity();
ToRotationMatrixWrapper<Quaternion<Scalar> > quatmat(quat);
Matrix<Scalar,3,3> mat33; mat33.setRandom();
cout.precision(4);
std::cout
<< "N ";
for(int i=0;i<SIZE;++i)
{
cout.width(9);
cout << i+1 << " ";
}
cout << "\n";
bench("matrix 3x3", mat33);
bench("quaternion", quat);
bench("quat-mat ", quatmat);
bench("isometry3 ", iso3);
bench("affine3 ", aff3);
bench("c affine3 ", caff3);
bench("proj3 ", proj3);
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/benchBlasGemm.cpp | .cpp | 6,313 | 220 | // g++ -O3 -DNDEBUG -I.. -L /usr/lib64/atlas/ benchBlasGemm.cpp -o benchBlasGemm -lrt -lcblas
// possible options:
// -DEIGEN_DONT_VECTORIZE
// -msse2
// #define EIGEN_DEFAULT_TO_ROW_MAJOR
#define _FLOAT
#include <iostream>
#include <Eigen/Core>
#include "BenchTimer.h"
// include the BLAS headers
extern "C" {
#include <cblas.h>
}
#include <string>
#ifdef _FLOAT
typedef float Scalar;
#define CBLAS_GEMM cblas_sgemm
#else
typedef double Scalar;
#define CBLAS_GEMM cblas_dgemm
#endif
typedef Eigen::Matrix<Scalar,Eigen::Dynamic,Eigen::Dynamic> MyMatrix;
void bench_eigengemm(MyMatrix& mc, const MyMatrix& ma, const MyMatrix& mb, int nbloops);
void check_product(int M, int N, int K);
void check_product(void);
int main(int argc, char *argv[])
{
// disable SSE exceptions
#ifdef __GNUC__
{
int aux;
asm(
"stmxcsr %[aux] \n\t"
"orl $32832, %[aux] \n\t"
"ldmxcsr %[aux] \n\t"
: : [aux] "m" (aux));
}
#endif
int nbtries=1, nbloops=1, M, N, K;
if (argc==2)
{
if (std::string(argv[1])=="check")
check_product();
else
M = N = K = atoi(argv[1]);
}
else if ((argc==3) && (std::string(argv[1])=="auto"))
{
M = N = K = atoi(argv[2]);
nbloops = 1000000000/(M*M*M);
if (nbloops<1)
nbloops = 1;
nbtries = 6;
}
else if (argc==4)
{
M = N = K = atoi(argv[1]);
nbloops = atoi(argv[2]);
nbtries = atoi(argv[3]);
}
else if (argc==6)
{
M = atoi(argv[1]);
N = atoi(argv[2]);
K = atoi(argv[3]);
nbloops = atoi(argv[4]);
nbtries = atoi(argv[5]);
}
else
{
std::cout << "Usage: " << argv[0] << " size \n";
std::cout << "Usage: " << argv[0] << " auto size\n";
std::cout << "Usage: " << argv[0] << " size nbloops nbtries\n";
std::cout << "Usage: " << argv[0] << " M N K nbloops nbtries\n";
std::cout << "Usage: " << argv[0] << " check\n";
std::cout << "Options:\n";
std::cout << " size unique size of the 2 matrices (integer)\n";
std::cout << " auto automatically set the number of repetitions and tries\n";
std::cout << " nbloops number of times the GEMM routines is executed\n";
std::cout << " nbtries number of times the loop is benched (return the best try)\n";
std::cout << " M N K sizes of the matrices: MxN = MxK * KxN (integers)\n";
std::cout << " check check eigen product using cblas as a reference\n";
exit(1);
}
double nbmad = double(M) * double(N) * double(K) * double(nbloops);
if (!(std::string(argv[1])=="auto"))
std::cout << M << " x " << N << " x " << K << "\n";
Scalar alpha, beta;
MyMatrix ma(M,K), mb(K,N), mc(M,N);
ma = MyMatrix::Random(M,K);
mb = MyMatrix::Random(K,N);
mc = MyMatrix::Random(M,N);
Eigen::BenchTimer timer;
// we simply compute c += a*b, so:
alpha = 1;
beta = 1;
// bench cblas
// ROWS_A, COLS_B, COLS_A, 1.0, A, COLS_A, B, COLS_B, 0.0, C, COLS_B);
if (!(std::string(argv[1])=="auto"))
{
timer.reset();
for (uint k=0 ; k<nbtries ; ++k)
{
timer.start();
for (uint j=0 ; j<nbloops ; ++j)
#ifdef EIGEN_DEFAULT_TO_ROW_MAJOR
CBLAS_GEMM(CblasRowMajor, CblasNoTrans, CblasNoTrans, M, N, K, alpha, ma.data(), K, mb.data(), N, beta, mc.data(), N);
#else
CBLAS_GEMM(CblasColMajor, CblasNoTrans, CblasNoTrans, M, N, K, alpha, ma.data(), M, mb.data(), K, beta, mc.data(), M);
#endif
timer.stop();
}
if (!(std::string(argv[1])=="auto"))
std::cout << "cblas: " << timer.value() << " (" << 1e-3*floor(1e-6*nbmad/timer.value()) << " GFlops/s)\n";
else
std::cout << M << " : " << timer.value() << " ; " << 1e-3*floor(1e-6*nbmad/timer.value()) << "\n";
}
// clear
ma = MyMatrix::Random(M,K);
mb = MyMatrix::Random(K,N);
mc = MyMatrix::Random(M,N);
// eigen
// if (!(std::string(argv[1])=="auto"))
{
timer.reset();
for (uint k=0 ; k<nbtries ; ++k)
{
timer.start();
bench_eigengemm(mc, ma, mb, nbloops);
timer.stop();
}
if (!(std::string(argv[1])=="auto"))
std::cout << "eigen : " << timer.value() << " (" << 1e-3*floor(1e-6*nbmad/timer.value()) << " GFlops/s)\n";
else
std::cout << M << " : " << timer.value() << " ; " << 1e-3*floor(1e-6*nbmad/timer.value()) << "\n";
}
std::cout << "l1: " << Eigen::l1CacheSize() << std::endl;
std::cout << "l2: " << Eigen::l2CacheSize() << std::endl;
return 0;
}
using namespace Eigen;
void bench_eigengemm(MyMatrix& mc, const MyMatrix& ma, const MyMatrix& mb, int nbloops)
{
for (uint j=0 ; j<nbloops ; ++j)
mc.noalias() += ma * mb;
}
#define MYVERIFY(A,M) if (!(A)) { \
std::cout << "FAIL: " << M << "\n"; \
}
void check_product(int M, int N, int K)
{
MyMatrix ma(M,K), mb(K,N), mc(M,N), maT(K,M), mbT(N,K), meigen(M,N), mref(M,N);
ma = MyMatrix::Random(M,K);
mb = MyMatrix::Random(K,N);
maT = ma.transpose();
mbT = mb.transpose();
mc = MyMatrix::Random(M,N);
MyMatrix::Scalar eps = 1e-4;
meigen = mref = mc;
CBLAS_GEMM(CblasColMajor, CblasNoTrans, CblasNoTrans, M, N, K, 1, ma.data(), M, mb.data(), K, 1, mref.data(), M);
meigen += ma * mb;
MYVERIFY(meigen.isApprox(mref, eps),". * .");
meigen = mref = mc;
CBLAS_GEMM(CblasColMajor, CblasTrans, CblasNoTrans, M, N, K, 1, maT.data(), K, mb.data(), K, 1, mref.data(), M);
meigen += maT.transpose() * mb;
MYVERIFY(meigen.isApprox(mref, eps),"T * .");
meigen = mref = mc;
CBLAS_GEMM(CblasColMajor, CblasTrans, CblasTrans, M, N, K, 1, maT.data(), K, mbT.data(), N, 1, mref.data(), M);
meigen += (maT.transpose()) * (mbT.transpose());
MYVERIFY(meigen.isApprox(mref, eps),"T * T");
meigen = mref = mc;
CBLAS_GEMM(CblasColMajor, CblasNoTrans, CblasTrans, M, N, K, 1, ma.data(), M, mbT.data(), N, 1, mref.data(), M);
meigen += ma * mbT.transpose();
MYVERIFY(meigen.isApprox(mref, eps),". * T");
}
void check_product(void)
{
int M, N, K;
for (uint i=0; i<1000; ++i)
{
M = internal::random<int>(1,64);
N = internal::random<int>(1,768);
K = internal::random<int>(1,768);
M = (0 + M) * 1;
std::cout << M << " x " << N << " x " << K << "\n";
check_product(M, N, K);
}
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/bench_gemm.cpp | .cpp | 10,885 | 342 |
// g++-4.4 bench_gemm.cpp -I .. -O2 -DNDEBUG -lrt -fopenmp && OMP_NUM_THREADS=2 ./a.out
// icpc bench_gemm.cpp -I .. -O3 -DNDEBUG -lrt -openmp && OMP_NUM_THREADS=2 ./a.out
// Compilation options:
//
// -DSCALAR=std::complex<double>
// -DSCALARA=double or -DSCALARB=double
// -DHAVE_BLAS
// -DDECOUPLED
//
#include <iostream>
#include <Eigen/Core>
#include <bench/BenchTimer.h>
using namespace std;
using namespace Eigen;
#ifndef SCALAR
// #define SCALAR std::complex<float>
#define SCALAR float
#endif
#ifndef SCALARA
#define SCALARA SCALAR
#endif
#ifndef SCALARB
#define SCALARB SCALAR
#endif
typedef SCALAR Scalar;
typedef NumTraits<Scalar>::Real RealScalar;
typedef Matrix<SCALARA,Dynamic,Dynamic> A;
typedef Matrix<SCALARB,Dynamic,Dynamic> B;
typedef Matrix<Scalar,Dynamic,Dynamic> C;
typedef Matrix<RealScalar,Dynamic,Dynamic> M;
#ifdef HAVE_BLAS
extern "C" {
#include <Eigen/src/misc/blas.h>
}
static float fone = 1;
static float fzero = 0;
static double done = 1;
static double szero = 0;
static std::complex<float> cfone = 1;
static std::complex<float> cfzero = 0;
static std::complex<double> cdone = 1;
static std::complex<double> cdzero = 0;
static char notrans = 'N';
static char trans = 'T';
static char nonunit = 'N';
static char lower = 'L';
static char right = 'R';
static int intone = 1;
void blas_gemm(const MatrixXf& a, const MatrixXf& b, MatrixXf& c)
{
int M = c.rows(); int N = c.cols(); int K = a.cols();
int lda = a.rows(); int ldb = b.rows(); int ldc = c.rows();
sgemm_(¬rans,¬rans,&M,&N,&K,&fone,
const_cast<float*>(a.data()),&lda,
const_cast<float*>(b.data()),&ldb,&fone,
c.data(),&ldc);
}
EIGEN_DONT_INLINE void blas_gemm(const MatrixXd& a, const MatrixXd& b, MatrixXd& c)
{
int M = c.rows(); int N = c.cols(); int K = a.cols();
int lda = a.rows(); int ldb = b.rows(); int ldc = c.rows();
dgemm_(¬rans,¬rans,&M,&N,&K,&done,
const_cast<double*>(a.data()),&lda,
const_cast<double*>(b.data()),&ldb,&done,
c.data(),&ldc);
}
void blas_gemm(const MatrixXcf& a, const MatrixXcf& b, MatrixXcf& c)
{
int M = c.rows(); int N = c.cols(); int K = a.cols();
int lda = a.rows(); int ldb = b.rows(); int ldc = c.rows();
cgemm_(¬rans,¬rans,&M,&N,&K,(float*)&cfone,
const_cast<float*>((const float*)a.data()),&lda,
const_cast<float*>((const float*)b.data()),&ldb,(float*)&cfone,
(float*)c.data(),&ldc);
}
void blas_gemm(const MatrixXcd& a, const MatrixXcd& b, MatrixXcd& c)
{
int M = c.rows(); int N = c.cols(); int K = a.cols();
int lda = a.rows(); int ldb = b.rows(); int ldc = c.rows();
zgemm_(¬rans,¬rans,&M,&N,&K,(double*)&cdone,
const_cast<double*>((const double*)a.data()),&lda,
const_cast<double*>((const double*)b.data()),&ldb,(double*)&cdone,
(double*)c.data(),&ldc);
}
#endif
void matlab_cplx_cplx(const M& ar, const M& ai, const M& br, const M& bi, M& cr, M& ci)
{
cr.noalias() += ar * br;
cr.noalias() -= ai * bi;
ci.noalias() += ar * bi;
ci.noalias() += ai * br;
// [cr ci] += [ar ai] * br + [-ai ar] * bi
}
void matlab_real_cplx(const M& a, const M& br, const M& bi, M& cr, M& ci)
{
cr.noalias() += a * br;
ci.noalias() += a * bi;
}
void matlab_cplx_real(const M& ar, const M& ai, const M& b, M& cr, M& ci)
{
cr.noalias() += ar * b;
ci.noalias() += ai * b;
}
template<typename A, typename B, typename C>
EIGEN_DONT_INLINE void gemm(const A& a, const B& b, C& c)
{
c.noalias() += a * b;
}
int main(int argc, char ** argv)
{
std::ptrdiff_t l1 = internal::queryL1CacheSize();
std::ptrdiff_t l2 = internal::queryTopLevelCacheSize();
std::cout << "L1 cache size = " << (l1>0 ? l1/1024 : -1) << " KB\n";
std::cout << "L2/L3 cache size = " << (l2>0 ? l2/1024 : -1) << " KB\n";
typedef internal::gebp_traits<Scalar,Scalar> Traits;
std::cout << "Register blocking = " << Traits::mr << " x " << Traits::nr << "\n";
int rep = 1; // number of repetitions per try
int tries = 2; // number of tries, we keep the best
int s = 2048;
int m = s;
int n = s;
int p = s;
int cache_size1=-1, cache_size2=l2, cache_size3 = 0;
bool need_help = false;
for (int i=1; i<argc;)
{
if(argv[i][0]=='-')
{
if(argv[i][1]=='s')
{
++i;
s = atoi(argv[i++]);
m = n = p = s;
if(argv[i][0]!='-')
{
n = atoi(argv[i++]);
p = atoi(argv[i++]);
}
}
else if(argv[i][1]=='c')
{
++i;
cache_size1 = atoi(argv[i++]);
if(argv[i][0]!='-')
{
cache_size2 = atoi(argv[i++]);
if(argv[i][0]!='-')
cache_size3 = atoi(argv[i++]);
}
}
else if(argv[i][1]=='t')
{
++i;
tries = atoi(argv[i++]);
}
else if(argv[i][1]=='p')
{
++i;
rep = atoi(argv[i++]);
}
}
else
{
need_help = true;
break;
}
}
if(need_help)
{
std::cout << argv[0] << " -s <matrix sizes> -c <cache sizes> -t <nb tries> -p <nb repeats>\n";
std::cout << " <matrix sizes> : size\n";
std::cout << " <matrix sizes> : rows columns depth\n";
return 1;
}
#if EIGEN_VERSION_AT_LEAST(3,2,90)
if(cache_size1>0)
setCpuCacheSizes(cache_size1,cache_size2,cache_size3);
#endif
A a(m,p); a.setRandom();
B b(p,n); b.setRandom();
C c(m,n); c.setOnes();
C rc = c;
std::cout << "Matrix sizes = " << m << "x" << p << " * " << p << "x" << n << "\n";
std::ptrdiff_t mc(m), nc(n), kc(p);
internal::computeProductBlockingSizes<Scalar,Scalar>(kc, mc, nc);
std::cout << "blocking size (mc x kc) = " << mc << " x " << kc << "\n";
C r = c;
// check the parallel product is correct
#if defined EIGEN_HAS_OPENMP
Eigen::initParallel();
int procs = omp_get_max_threads();
if(procs>1)
{
#ifdef HAVE_BLAS
blas_gemm(a,b,r);
#else
omp_set_num_threads(1);
r.noalias() += a * b;
omp_set_num_threads(procs);
#endif
c.noalias() += a * b;
if(!r.isApprox(c)) std::cerr << "Warning, your parallel product is crap!\n\n";
}
#elif defined HAVE_BLAS
blas_gemm(a,b,r);
c.noalias() += a * b;
if(!r.isApprox(c)) {
std::cout << (r - c).norm() << "\n";
std::cerr << "Warning, your product is crap!\n\n";
}
#else
if(1.*m*n*p<2000.*2000*2000)
{
gemm(a,b,c);
r.noalias() += a.cast<Scalar>() .lazyProduct( b.cast<Scalar>() );
if(!r.isApprox(c)) {
std::cout << (r - c).norm() << "\n";
std::cerr << "Warning, your product is crap!\n\n";
}
}
#endif
#ifdef HAVE_BLAS
BenchTimer tblas;
c = rc;
BENCH(tblas, tries, rep, blas_gemm(a,b,c));
std::cout << "blas cpu " << tblas.best(CPU_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/tblas.best(CPU_TIMER))*1e-9 << " GFLOPS \t(" << tblas.total(CPU_TIMER) << "s)\n";
std::cout << "blas real " << tblas.best(REAL_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/tblas.best(REAL_TIMER))*1e-9 << " GFLOPS \t(" << tblas.total(REAL_TIMER) << "s)\n";
#endif
BenchTimer tmt;
c = rc;
BENCH(tmt, tries, rep, gemm(a,b,c));
std::cout << "eigen cpu " << tmt.best(CPU_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/tmt.best(CPU_TIMER))*1e-9 << " GFLOPS \t(" << tmt.total(CPU_TIMER) << "s)\n";
std::cout << "eigen real " << tmt.best(REAL_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/tmt.best(REAL_TIMER))*1e-9 << " GFLOPS \t(" << tmt.total(REAL_TIMER) << "s)\n";
#ifdef EIGEN_HAS_OPENMP
if(procs>1)
{
BenchTimer tmono;
omp_set_num_threads(1);
Eigen::setNbThreads(1);
c = rc;
BENCH(tmono, tries, rep, gemm(a,b,c));
std::cout << "eigen mono cpu " << tmono.best(CPU_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/tmono.best(CPU_TIMER))*1e-9 << " GFLOPS \t(" << tmono.total(CPU_TIMER) << "s)\n";
std::cout << "eigen mono real " << tmono.best(REAL_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/tmono.best(REAL_TIMER))*1e-9 << " GFLOPS \t(" << tmono.total(REAL_TIMER) << "s)\n";
std::cout << "mt speed up x" << tmono.best(CPU_TIMER) / tmt.best(REAL_TIMER) << " => " << (100.0*tmono.best(CPU_TIMER) / tmt.best(REAL_TIMER))/procs << "%\n";
}
#endif
if(1.*m*n*p<30*30*30)
{
BenchTimer tmt;
c = rc;
BENCH(tmt, tries, rep, c.noalias()+=a.lazyProduct(b));
std::cout << "lazy cpu " << tmt.best(CPU_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/tmt.best(CPU_TIMER))*1e-9 << " GFLOPS \t(" << tmt.total(CPU_TIMER) << "s)\n";
std::cout << "lazy real " << tmt.best(REAL_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/tmt.best(REAL_TIMER))*1e-9 << " GFLOPS \t(" << tmt.total(REAL_TIMER) << "s)\n";
}
#ifdef DECOUPLED
if((NumTraits<A::Scalar>::IsComplex) && (NumTraits<B::Scalar>::IsComplex))
{
M ar(m,p); ar.setRandom();
M ai(m,p); ai.setRandom();
M br(p,n); br.setRandom();
M bi(p,n); bi.setRandom();
M cr(m,n); cr.setRandom();
M ci(m,n); ci.setRandom();
BenchTimer t;
BENCH(t, tries, rep, matlab_cplx_cplx(ar,ai,br,bi,cr,ci));
std::cout << "\"matlab\" cpu " << t.best(CPU_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/t.best(CPU_TIMER))*1e-9 << " GFLOPS \t(" << t.total(CPU_TIMER) << "s)\n";
std::cout << "\"matlab\" real " << t.best(REAL_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/t.best(REAL_TIMER))*1e-9 << " GFLOPS \t(" << t.total(REAL_TIMER) << "s)\n";
}
if((!NumTraits<A::Scalar>::IsComplex) && (NumTraits<B::Scalar>::IsComplex))
{
M a(m,p); a.setRandom();
M br(p,n); br.setRandom();
M bi(p,n); bi.setRandom();
M cr(m,n); cr.setRandom();
M ci(m,n); ci.setRandom();
BenchTimer t;
BENCH(t, tries, rep, matlab_real_cplx(a,br,bi,cr,ci));
std::cout << "\"matlab\" cpu " << t.best(CPU_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/t.best(CPU_TIMER))*1e-9 << " GFLOPS \t(" << t.total(CPU_TIMER) << "s)\n";
std::cout << "\"matlab\" real " << t.best(REAL_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/t.best(REAL_TIMER))*1e-9 << " GFLOPS \t(" << t.total(REAL_TIMER) << "s)\n";
}
if((NumTraits<A::Scalar>::IsComplex) && (!NumTraits<B::Scalar>::IsComplex))
{
M ar(m,p); ar.setRandom();
M ai(m,p); ai.setRandom();
M b(p,n); b.setRandom();
M cr(m,n); cr.setRandom();
M ci(m,n); ci.setRandom();
BenchTimer t;
BENCH(t, tries, rep, matlab_cplx_real(ar,ai,b,cr,ci));
std::cout << "\"matlab\" cpu " << t.best(CPU_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/t.best(CPU_TIMER))*1e-9 << " GFLOPS \t(" << t.total(CPU_TIMER) << "s)\n";
std::cout << "\"matlab\" real " << t.best(REAL_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/t.best(REAL_TIMER))*1e-9 << " GFLOPS \t(" << t.total(REAL_TIMER) << "s)\n";
}
#endif
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/benchmarkSlice.cpp | .cpp | 835 | 39 | // g++ -O3 -DNDEBUG benchmarkX.cpp -o benchmarkX && time ./benchmarkX
#include <iostream>
#include <Eigen/Core>
using namespace std;
using namespace Eigen;
#ifndef REPEAT
#define REPEAT 10000
#endif
#ifndef SCALAR
#define SCALAR float
#endif
int main(int argc, char *argv[])
{
typedef Matrix<SCALAR, Eigen::Dynamic, Eigen::Dynamic> Mat;
Mat m(100, 100);
m.setRandom();
for(int a = 0; a < REPEAT; a++)
{
int r, c, nr, nc;
r = Eigen::internal::random<int>(0,10);
c = Eigen::internal::random<int>(0,10);
nr = Eigen::internal::random<int>(50,80);
nc = Eigen::internal::random<int>(50,80);
m.block(r,c,nr,nc) += Mat::Ones(nr,nc);
m.block(r,c,nr,nc) *= SCALAR(10);
m.block(r,c,nr,nc) -= Mat::constant(nr,nc,10);
m.block(r,c,nr,nc) /= SCALAR(10);
}
cout << m[0] << endl;
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/quatmul.cpp | .cpp | 1,097 | 48 | #include <iostream>
#include <Eigen/Core>
#include <Eigen/Geometry>
#include <bench/BenchTimer.h>
using namespace Eigen;
template<typename Quat>
EIGEN_DONT_INLINE void quatmul_default(const Quat& a, const Quat& b, Quat& c)
{
c = a * b;
}
template<typename Quat>
EIGEN_DONT_INLINE void quatmul_novec(const Quat& a, const Quat& b, Quat& c)
{
c = internal::quat_product<0, Quat, Quat, typename Quat::Scalar, Aligned>::run(a,b);
}
template<typename Quat> void bench(const std::string& label)
{
int tries = 10;
int rep = 1000000;
BenchTimer t;
Quat a(4, 1, 2, 3);
Quat b(2, 3, 4, 5);
Quat c;
std::cout.precision(3);
BENCH(t, tries, rep, quatmul_default(a,b,c));
std::cout << label << " default " << 1e3*t.best(CPU_TIMER) << "ms \t" << 1e-6*double(rep)/(t.best(CPU_TIMER)) << " M mul/s\n";
BENCH(t, tries, rep, quatmul_novec(a,b,c));
std::cout << label << " novec " << 1e3*t.best(CPU_TIMER) << "ms \t" << 1e-6*double(rep)/(t.best(CPU_TIMER)) << " M mul/s\n";
}
int main()
{
bench<Quaternionf>("float ");
bench<Quaterniond>("double");
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/benchmarkXcwise.cpp | .cpp | 605 | 36 | // g++ -O3 -DNDEBUG benchmarkX.cpp -o benchmarkX && time ./benchmarkX
#include <iostream>
#include <Eigen/Core>
using namespace std;
using namespace Eigen;
#ifndef VECTYPE
#define VECTYPE VectorXLd
#endif
#ifndef VECSIZE
#define VECSIZE 1000000
#endif
#ifndef REPEAT
#define REPEAT 1000
#endif
int main(int argc, char *argv[])
{
VECTYPE I = VECTYPE::Ones(VECSIZE);
VECTYPE m(VECSIZE,1);
for(int i = 0; i < VECSIZE; i++)
{
m[i] = 0.1 * i/VECSIZE;
}
for(int a = 0; a < REPEAT; a++)
{
m = VECTYPE::Ones(VECSIZE) + 0.00005 * (m.cwise().square() + m/4);
}
cout << m[0] << endl;
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/vdw_new.cpp | .cpp | 1,203 | 57 | #include <iostream>
#include <Eigen/Core>
using namespace Eigen;
#ifndef SCALAR
#define SCALAR float
#endif
#ifndef SIZE
#define SIZE 10000
#endif
#ifndef REPEAT
#define REPEAT 10000
#endif
typedef Matrix<SCALAR, Eigen::Dynamic, 1> Vec;
using namespace std;
SCALAR E_VDW(const Vec &interactions1, const Vec &interactions2)
{
return (interactions2.cwise()/interactions1)
.cwise().cube()
.cwise().square()
.cwise().square()
.sum();
}
int main()
{
//
// 1 2 3 4 ... (interactions)
// ka . . . . ...
// rab . . . . ...
// energy . . . . ...
// ... ... ... ... ... ...
// (variables
// for
// interaction)
//
Vec interactions1(SIZE), interactions2(SIZE); // SIZE is the number of vdw interactions in our system
// SetupCalculations()
SCALAR rab = 1.0;
interactions1.setConstant(2.4);
interactions2.setConstant(rab);
// Energy()
SCALAR energy = 0.0;
for (unsigned int i = 0; i<REPEAT; ++i) {
energy += E_VDW(interactions1, interactions2);
energy *= 1 + 1e-20 * i; // prevent compiler from optimizing the loop
}
cout << "energy = " << energy << endl;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/bench_multi_compilers.sh | .sh | 618 | 29 | #!/bin/bash
if (($# < 2)); then
echo "Usage: $0 compilerlist.txt benchfile.cpp"
else
compilerlist=$1
benchfile=$2
g=0
source $compilerlist
# for each compiler, compile benchfile and run the benchmark
for (( i=0 ; i<g ; ++i )) ; do
# check the compiler exists
compiler=`echo ${CLIST[$i]} | cut -d " " -f 1`
if [ -e `which $compiler` ]; then
echo "${CLIST[$i]}"
# echo "${CLIST[$i]} $benchfile -I.. -o bench~"
# if [ -e ./.bench ] ; then rm .bench; fi
${CLIST[$i]} $benchfile -I.. -o .bench && ./.bench 2> /dev/null
echo ""
else
echo "compiler not found: $compiler"
fi
done
fi
| Shell |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/BenchUtil.h | .h | 2,529 | 93 |
#ifndef EIGEN_BENCH_UTIL_H
#define EIGEN_BENCH_UTIL_H
#include <Eigen/Core>
#include "BenchTimer.h"
using namespace std;
using namespace Eigen;
#include <boost/preprocessor/repetition/enum_params.hpp>
#include <boost/preprocessor/repetition.hpp>
#include <boost/preprocessor/seq.hpp>
#include <boost/preprocessor/array.hpp>
#include <boost/preprocessor/arithmetic.hpp>
#include <boost/preprocessor/comparison.hpp>
#include <boost/preprocessor/punctuation.hpp>
#include <boost/preprocessor/punctuation/comma.hpp>
#include <boost/preprocessor/stringize.hpp>
template<typename MatrixType> void initMatrix_random(MatrixType& mat) __attribute__((noinline));
template<typename MatrixType> void initMatrix_random(MatrixType& mat)
{
mat.setRandom();// = MatrixType::random(mat.rows(), mat.cols());
}
template<typename MatrixType> void initMatrix_identity(MatrixType& mat) __attribute__((noinline));
template<typename MatrixType> void initMatrix_identity(MatrixType& mat)
{
mat.setIdentity();
}
#ifndef __INTEL_COMPILER
#define DISABLE_SSE_EXCEPTIONS() { \
int aux; \
asm( \
"stmxcsr %[aux] \n\t" \
"orl $32832, %[aux] \n\t" \
"ldmxcsr %[aux] \n\t" \
: : [aux] "m" (aux)); \
}
#else
#define DISABLE_SSE_EXCEPTIONS()
#endif
#ifdef BENCH_GMM
#include <gmm/gmm.h>
template <typename EigenMatrixType, typename GmmMatrixType>
void eiToGmm(const EigenMatrixType& src, GmmMatrixType& dst)
{
dst.resize(src.rows(),src.cols());
for (int j=0; j<src.cols(); ++j)
for (int i=0; i<src.rows(); ++i)
dst(i,j) = src.coeff(i,j);
}
#endif
#ifdef BENCH_GSL
#include <gsl/gsl_matrix.h>
#include <gsl/gsl_linalg.h>
#include <gsl/gsl_eigen.h>
template <typename EigenMatrixType>
void eiToGsl(const EigenMatrixType& src, gsl_matrix** dst)
{
for (int j=0; j<src.cols(); ++j)
for (int i=0; i<src.rows(); ++i)
gsl_matrix_set(*dst, i, j, src.coeff(i,j));
}
#endif
#ifdef BENCH_UBLAS
#include <boost/numeric/ublas/matrix.hpp>
#include <boost/numeric/ublas/vector.hpp>
template <typename EigenMatrixType, typename UblasMatrixType>
void eiToUblas(const EigenMatrixType& src, UblasMatrixType& dst)
{
dst.resize(src.rows(),src.cols());
for (int j=0; j<src.cols(); ++j)
for (int i=0; i<src.rows(); ++i)
dst(i,j) = src.coeff(i,j);
}
template <typename EigenType, typename UblasType>
void eiToUblasVec(const EigenType& src, UblasType& dst)
{
dst.resize(src.size());
for (int j=0; j<src.size(); ++j)
dst[j] = src.coeff(j);
}
#endif
#endif // EIGEN_BENCH_UTIL_H
| Unknown |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/analyze-blocking-sizes.cpp | .cpp | 28,983 | 877 | // This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2015 Benoit Jacob <benoitjacob@google.com>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
#include <iostream>
#include <cstdint>
#include <cstdlib>
#include <vector>
#include <algorithm>
#include <fstream>
#include <string>
#include <cmath>
#include <cassert>
#include <cstring>
#include <memory>
#include <Eigen/Core>
using namespace std;
const int default_precision = 4;
// see --only-cubic-sizes
bool only_cubic_sizes = false;
// see --dump-tables
bool dump_tables = false;
uint8_t log2_pot(size_t x) {
size_t l = 0;
while (x >>= 1) l++;
return l;
}
uint16_t compact_size_triple(size_t k, size_t m, size_t n)
{
return (log2_pot(k) << 8) | (log2_pot(m) << 4) | log2_pot(n);
}
// just a helper to store a triple of K,M,N sizes for matrix product
struct size_triple_t
{
uint16_t k, m, n;
size_triple_t() : k(0), m(0), n(0) {}
size_triple_t(size_t _k, size_t _m, size_t _n) : k(_k), m(_m), n(_n) {}
size_triple_t(const size_triple_t& o) : k(o.k), m(o.m), n(o.n) {}
size_triple_t(uint16_t compact)
{
k = 1 << ((compact & 0xf00) >> 8);
m = 1 << ((compact & 0x0f0) >> 4);
n = 1 << ((compact & 0x00f) >> 0);
}
bool is_cubic() const { return k == m && m == n; }
};
ostream& operator<<(ostream& s, const size_triple_t& t)
{
return s << "(" << t.k << ", " << t.m << ", " << t.n << ")";
}
struct inputfile_entry_t
{
uint16_t product_size;
uint16_t pot_block_size;
size_triple_t nonpot_block_size;
float gflops;
};
struct inputfile_t
{
enum class type_t {
unknown,
all_pot_sizes,
default_sizes
};
string filename;
vector<inputfile_entry_t> entries;
type_t type;
inputfile_t(const string& fname)
: filename(fname)
, type(type_t::unknown)
{
ifstream stream(filename);
if (!stream.is_open()) {
cerr << "couldn't open input file: " << filename << endl;
exit(1);
}
string line;
while (getline(stream, line)) {
if (line.empty()) continue;
if (line.find("BEGIN MEASUREMENTS ALL POT SIZES") == 0) {
if (type != type_t::unknown) {
cerr << "Input file " << filename << " contains redundant BEGIN MEASUREMENTS lines";
exit(1);
}
type = type_t::all_pot_sizes;
continue;
}
if (line.find("BEGIN MEASUREMENTS DEFAULT SIZES") == 0) {
if (type != type_t::unknown) {
cerr << "Input file " << filename << " contains redundant BEGIN MEASUREMENTS lines";
exit(1);
}
type = type_t::default_sizes;
continue;
}
if (type == type_t::unknown) {
continue;
}
switch(type) {
case type_t::all_pot_sizes: {
unsigned int product_size, block_size;
float gflops;
int sscanf_result =
sscanf(line.c_str(), "%x %x %f",
&product_size,
&block_size,
&gflops);
if (3 != sscanf_result ||
!product_size ||
product_size > 0xfff ||
!block_size ||
block_size > 0xfff ||
!isfinite(gflops))
{
cerr << "ill-formed input file: " << filename << endl;
cerr << "offending line:" << endl << line << endl;
exit(1);
}
if (only_cubic_sizes && !size_triple_t(product_size).is_cubic()) {
continue;
}
inputfile_entry_t entry;
entry.product_size = uint16_t(product_size);
entry.pot_block_size = uint16_t(block_size);
entry.gflops = gflops;
entries.push_back(entry);
break;
}
case type_t::default_sizes: {
unsigned int product_size;
float gflops;
int bk, bm, bn;
int sscanf_result =
sscanf(line.c_str(), "%x default(%d, %d, %d) %f",
&product_size,
&bk, &bm, &bn,
&gflops);
if (5 != sscanf_result ||
!product_size ||
product_size > 0xfff ||
!isfinite(gflops))
{
cerr << "ill-formed input file: " << filename << endl;
cerr << "offending line:" << endl << line << endl;
exit(1);
}
if (only_cubic_sizes && !size_triple_t(product_size).is_cubic()) {
continue;
}
inputfile_entry_t entry;
entry.product_size = uint16_t(product_size);
entry.pot_block_size = 0;
entry.nonpot_block_size = size_triple_t(bk, bm, bn);
entry.gflops = gflops;
entries.push_back(entry);
break;
}
default:
break;
}
}
stream.close();
if (type == type_t::unknown) {
cerr << "Unrecognized input file " << filename << endl;
exit(1);
}
if (entries.empty()) {
cerr << "didn't find any measurements in input file: " << filename << endl;
exit(1);
}
}
};
struct preprocessed_inputfile_entry_t
{
uint16_t product_size;
uint16_t block_size;
float efficiency;
};
bool lower_efficiency(const preprocessed_inputfile_entry_t& e1, const preprocessed_inputfile_entry_t& e2)
{
return e1.efficiency < e2.efficiency;
}
struct preprocessed_inputfile_t
{
string filename;
vector<preprocessed_inputfile_entry_t> entries;
preprocessed_inputfile_t(const inputfile_t& inputfile)
: filename(inputfile.filename)
{
if (inputfile.type != inputfile_t::type_t::all_pot_sizes) {
abort();
}
auto it = inputfile.entries.begin();
auto it_first_with_given_product_size = it;
while (it != inputfile.entries.end()) {
++it;
if (it == inputfile.entries.end() ||
it->product_size != it_first_with_given_product_size->product_size)
{
import_input_file_range_one_product_size(it_first_with_given_product_size, it);
it_first_with_given_product_size = it;
}
}
}
private:
void import_input_file_range_one_product_size(
const vector<inputfile_entry_t>::const_iterator& begin,
const vector<inputfile_entry_t>::const_iterator& end)
{
uint16_t product_size = begin->product_size;
float max_gflops = 0.0f;
for (auto it = begin; it != end; ++it) {
if (it->product_size != product_size) {
cerr << "Unexpected ordering of entries in " << filename << endl;
cerr << "(Expected all entries for product size " << hex << product_size << dec << " to be grouped)" << endl;
exit(1);
}
max_gflops = max(max_gflops, it->gflops);
}
for (auto it = begin; it != end; ++it) {
preprocessed_inputfile_entry_t entry;
entry.product_size = it->product_size;
entry.block_size = it->pot_block_size;
entry.efficiency = it->gflops / max_gflops;
entries.push_back(entry);
}
}
};
void check_all_files_in_same_exact_order(
const vector<preprocessed_inputfile_t>& preprocessed_inputfiles)
{
if (preprocessed_inputfiles.empty()) {
return;
}
const preprocessed_inputfile_t& first_file = preprocessed_inputfiles[0];
const size_t num_entries = first_file.entries.size();
for (size_t i = 0; i < preprocessed_inputfiles.size(); i++) {
if (preprocessed_inputfiles[i].entries.size() != num_entries) {
cerr << "these files have different number of entries: "
<< preprocessed_inputfiles[i].filename
<< " and "
<< first_file.filename
<< endl;
exit(1);
}
}
for (size_t entry_index = 0; entry_index < num_entries; entry_index++) {
const uint16_t entry_product_size = first_file.entries[entry_index].product_size;
const uint16_t entry_block_size = first_file.entries[entry_index].block_size;
for (size_t file_index = 0; file_index < preprocessed_inputfiles.size(); file_index++) {
const preprocessed_inputfile_t& cur_file = preprocessed_inputfiles[file_index];
if (cur_file.entries[entry_index].product_size != entry_product_size ||
cur_file.entries[entry_index].block_size != entry_block_size)
{
cerr << "entries not in same order between these files: "
<< first_file.filename
<< " and "
<< cur_file.filename
<< endl;
exit(1);
}
}
}
}
float efficiency_of_subset(
const vector<preprocessed_inputfile_t>& preprocessed_inputfiles,
const vector<size_t>& subset)
{
if (subset.size() <= 1) {
return 1.0f;
}
const preprocessed_inputfile_t& first_file = preprocessed_inputfiles[subset[0]];
const size_t num_entries = first_file.entries.size();
float efficiency = 1.0f;
size_t entry_index = 0;
size_t first_entry_index_with_this_product_size = 0;
uint16_t product_size = first_file.entries[0].product_size;
while (entry_index < num_entries) {
++entry_index;
if (entry_index == num_entries ||
first_file.entries[entry_index].product_size != product_size)
{
float efficiency_this_product_size = 0.0f;
for (size_t e = first_entry_index_with_this_product_size; e < entry_index; e++) {
float efficiency_this_entry = 1.0f;
for (auto i = subset.begin(); i != subset.end(); ++i) {
efficiency_this_entry = min(efficiency_this_entry, preprocessed_inputfiles[*i].entries[e].efficiency);
}
efficiency_this_product_size = max(efficiency_this_product_size, efficiency_this_entry);
}
efficiency = min(efficiency, efficiency_this_product_size);
if (entry_index < num_entries) {
first_entry_index_with_this_product_size = entry_index;
product_size = first_file.entries[entry_index].product_size;
}
}
}
return efficiency;
}
void dump_table_for_subset(
const vector<preprocessed_inputfile_t>& preprocessed_inputfiles,
const vector<size_t>& subset)
{
const preprocessed_inputfile_t& first_file = preprocessed_inputfiles[subset[0]];
const size_t num_entries = first_file.entries.size();
size_t entry_index = 0;
size_t first_entry_index_with_this_product_size = 0;
uint16_t product_size = first_file.entries[0].product_size;
size_t i = 0;
size_triple_t min_product_size(first_file.entries.front().product_size);
size_triple_t max_product_size(first_file.entries.back().product_size);
if (!min_product_size.is_cubic() || !max_product_size.is_cubic()) {
abort();
}
if (only_cubic_sizes) {
cerr << "Can't generate tables with --only-cubic-sizes." << endl;
abort();
}
cout << "struct LookupTable {" << endl;
cout << " static const size_t BaseSize = " << min_product_size.k << ";" << endl;
const size_t NumSizes = log2_pot(max_product_size.k / min_product_size.k) + 1;
const size_t TableSize = NumSizes * NumSizes * NumSizes;
cout << " static const size_t NumSizes = " << NumSizes << ";" << endl;
cout << " static const unsigned short* Data() {" << endl;
cout << " static const unsigned short data[" << TableSize << "] = {";
while (entry_index < num_entries) {
++entry_index;
if (entry_index == num_entries ||
first_file.entries[entry_index].product_size != product_size)
{
float best_efficiency_this_product_size = 0.0f;
uint16_t best_block_size_this_product_size = 0;
for (size_t e = first_entry_index_with_this_product_size; e < entry_index; e++) {
float efficiency_this_entry = 1.0f;
for (auto i = subset.begin(); i != subset.end(); ++i) {
efficiency_this_entry = min(efficiency_this_entry, preprocessed_inputfiles[*i].entries[e].efficiency);
}
if (efficiency_this_entry > best_efficiency_this_product_size) {
best_efficiency_this_product_size = efficiency_this_entry;
best_block_size_this_product_size = first_file.entries[e].block_size;
}
}
if ((i++) % NumSizes) {
cout << " ";
} else {
cout << endl << " ";
}
cout << "0x" << hex << best_block_size_this_product_size << dec;
if (entry_index < num_entries) {
cout << ",";
first_entry_index_with_this_product_size = entry_index;
product_size = first_file.entries[entry_index].product_size;
}
}
}
if (i != TableSize) {
cerr << endl << "Wrote " << i << " table entries, expected " << TableSize << endl;
abort();
}
cout << endl << " };" << endl;
cout << " return data;" << endl;
cout << " }" << endl;
cout << "};" << endl;
}
float efficiency_of_partition(
const vector<preprocessed_inputfile_t>& preprocessed_inputfiles,
const vector<vector<size_t>>& partition)
{
float efficiency = 1.0f;
for (auto s = partition.begin(); s != partition.end(); ++s) {
efficiency = min(efficiency, efficiency_of_subset(preprocessed_inputfiles, *s));
}
return efficiency;
}
void make_first_subset(size_t subset_size, vector<size_t>& out_subset, size_t set_size)
{
assert(subset_size >= 1 && subset_size <= set_size);
out_subset.resize(subset_size);
for (size_t i = 0; i < subset_size; i++) {
out_subset[i] = i;
}
}
bool is_last_subset(const vector<size_t>& subset, size_t set_size)
{
return subset[0] == set_size - subset.size();
}
void next_subset(vector<size_t>& inout_subset, size_t set_size)
{
if (is_last_subset(inout_subset, set_size)) {
cerr << "iterating past the last subset" << endl;
abort();
}
size_t i = 1;
while (inout_subset[inout_subset.size() - i] == set_size - i) {
i++;
assert(i <= inout_subset.size());
}
size_t first_index_to_change = inout_subset.size() - i;
inout_subset[first_index_to_change]++;
size_t p = inout_subset[first_index_to_change];
for (size_t j = first_index_to_change + 1; j < inout_subset.size(); j++) {
inout_subset[j] = ++p;
}
}
const size_t number_of_subsets_limit = 100;
const size_t always_search_subsets_of_size_at_least = 2;
bool is_number_of_subsets_feasible(size_t n, size_t p)
{
assert(n>0 && p>0 && p<=n);
uint64_t numerator = 1, denominator = 1;
for (size_t i = 0; i < p; i++) {
numerator *= n - i;
denominator *= i + 1;
if (numerator > denominator * number_of_subsets_limit) {
return false;
}
}
return true;
}
size_t max_feasible_subset_size(size_t n)
{
assert(n > 0);
const size_t minresult = min<size_t>(n-1, always_search_subsets_of_size_at_least);
for (size_t p = 1; p <= n - 1; p++) {
if (!is_number_of_subsets_feasible(n, p+1)) {
return max(p, minresult);
}
}
return n - 1;
}
void find_subset_with_efficiency_higher_than(
const vector<preprocessed_inputfile_t>& preprocessed_inputfiles,
float required_efficiency_to_beat,
vector<size_t>& inout_remainder,
vector<size_t>& out_subset)
{
out_subset.resize(0);
if (required_efficiency_to_beat >= 1.0f) {
cerr << "can't beat efficiency 1." << endl;
abort();
}
while (!inout_remainder.empty()) {
vector<size_t> candidate_indices(inout_remainder.size());
for (size_t i = 0; i < candidate_indices.size(); i++) {
candidate_indices[i] = i;
}
size_t candidate_indices_subset_size = max_feasible_subset_size(candidate_indices.size());
while (candidate_indices_subset_size >= 1) {
vector<size_t> candidate_indices_subset;
make_first_subset(candidate_indices_subset_size,
candidate_indices_subset,
candidate_indices.size());
vector<size_t> best_candidate_indices_subset;
float best_efficiency = 0.0f;
vector<size_t> trial_subset = out_subset;
trial_subset.resize(out_subset.size() + candidate_indices_subset_size);
while (true)
{
for (size_t i = 0; i < candidate_indices_subset_size; i++) {
trial_subset[out_subset.size() + i] = inout_remainder[candidate_indices_subset[i]];
}
float trial_efficiency = efficiency_of_subset(preprocessed_inputfiles, trial_subset);
if (trial_efficiency > best_efficiency) {
best_efficiency = trial_efficiency;
best_candidate_indices_subset = candidate_indices_subset;
}
if (is_last_subset(candidate_indices_subset, candidate_indices.size())) {
break;
}
next_subset(candidate_indices_subset, candidate_indices.size());
}
if (best_efficiency > required_efficiency_to_beat) {
for (size_t i = 0; i < best_candidate_indices_subset.size(); i++) {
candidate_indices[i] = candidate_indices[best_candidate_indices_subset[i]];
}
candidate_indices.resize(best_candidate_indices_subset.size());
}
candidate_indices_subset_size--;
}
size_t candidate_index = candidate_indices[0];
auto candidate_iterator = inout_remainder.begin() + candidate_index;
vector<size_t> trial_subset = out_subset;
trial_subset.push_back(*candidate_iterator);
float trial_efficiency = efficiency_of_subset(preprocessed_inputfiles, trial_subset);
if (trial_efficiency > required_efficiency_to_beat) {
out_subset.push_back(*candidate_iterator);
inout_remainder.erase(candidate_iterator);
} else {
break;
}
}
}
void find_partition_with_efficiency_higher_than(
const vector<preprocessed_inputfile_t>& preprocessed_inputfiles,
float required_efficiency_to_beat,
vector<vector<size_t>>& out_partition)
{
out_partition.resize(0);
vector<size_t> remainder;
for (size_t i = 0; i < preprocessed_inputfiles.size(); i++) {
remainder.push_back(i);
}
while (!remainder.empty()) {
vector<size_t> new_subset;
find_subset_with_efficiency_higher_than(
preprocessed_inputfiles,
required_efficiency_to_beat,
remainder,
new_subset);
out_partition.push_back(new_subset);
}
}
void print_partition(
const vector<preprocessed_inputfile_t>& preprocessed_inputfiles,
const vector<vector<size_t>>& partition)
{
float efficiency = efficiency_of_partition(preprocessed_inputfiles, partition);
cout << "Partition into " << partition.size() << " subsets for " << efficiency * 100.0f << "% efficiency" << endl;
for (auto subset = partition.begin(); subset != partition.end(); ++subset) {
cout << " Subset " << (subset - partition.begin())
<< ", efficiency " << efficiency_of_subset(preprocessed_inputfiles, *subset) * 100.0f << "%:"
<< endl;
for (auto file = subset->begin(); file != subset->end(); ++file) {
cout << " " << preprocessed_inputfiles[*file].filename << endl;
}
if (dump_tables) {
cout << " Table:" << endl;
dump_table_for_subset(preprocessed_inputfiles, *subset);
}
}
cout << endl;
}
struct action_t
{
virtual const char* invokation_name() const { abort(); return nullptr; }
virtual void run(const vector<string>&) const { abort(); }
virtual ~action_t() {}
};
struct partition_action_t : action_t
{
virtual const char* invokation_name() const override { return "partition"; }
virtual void run(const vector<string>& input_filenames) const override
{
vector<preprocessed_inputfile_t> preprocessed_inputfiles;
if (input_filenames.empty()) {
cerr << "The " << invokation_name() << " action needs a list of input files." << endl;
exit(1);
}
for (auto it = input_filenames.begin(); it != input_filenames.end(); ++it) {
inputfile_t inputfile(*it);
switch (inputfile.type) {
case inputfile_t::type_t::all_pot_sizes:
preprocessed_inputfiles.emplace_back(inputfile);
break;
case inputfile_t::type_t::default_sizes:
cerr << "The " << invokation_name() << " action only uses measurements for all pot sizes, and "
<< "has no use for " << *it << " which contains measurements for default sizes." << endl;
exit(1);
break;
default:
cerr << "Unrecognized input file: " << *it << endl;
exit(1);
}
}
check_all_files_in_same_exact_order(preprocessed_inputfiles);
float required_efficiency_to_beat = 0.0f;
vector<vector<vector<size_t>>> partitions;
cerr << "searching for partitions...\r" << flush;
while (true)
{
vector<vector<size_t>> partition;
find_partition_with_efficiency_higher_than(
preprocessed_inputfiles,
required_efficiency_to_beat,
partition);
float actual_efficiency = efficiency_of_partition(preprocessed_inputfiles, partition);
cerr << "partition " << preprocessed_inputfiles.size() << " files into " << partition.size()
<< " subsets for " << 100.0f * actual_efficiency
<< " % efficiency"
<< " \r" << flush;
partitions.push_back(partition);
if (partition.size() == preprocessed_inputfiles.size() || actual_efficiency == 1.0f) {
break;
}
required_efficiency_to_beat = actual_efficiency;
}
cerr << " " << endl;
while (true) {
bool repeat = false;
for (size_t i = 0; i < partitions.size() - 1; i++) {
if (partitions[i].size() >= partitions[i+1].size()) {
partitions.erase(partitions.begin() + i);
repeat = true;
break;
}
}
if (!repeat) {
break;
}
}
for (auto it = partitions.begin(); it != partitions.end(); ++it) {
print_partition(preprocessed_inputfiles, *it);
}
}
};
struct evaluate_defaults_action_t : action_t
{
struct results_entry_t {
uint16_t product_size;
size_triple_t default_block_size;
uint16_t best_pot_block_size;
float default_gflops;
float best_pot_gflops;
float default_efficiency;
};
friend ostream& operator<<(ostream& s, const results_entry_t& entry)
{
return s
<< "Product size " << size_triple_t(entry.product_size)
<< ": default block size " << entry.default_block_size
<< " -> " << entry.default_gflops
<< " GFlop/s = " << entry.default_efficiency * 100.0f << " %"
<< " of best POT block size " << size_triple_t(entry.best_pot_block_size)
<< " -> " << entry.best_pot_gflops
<< " GFlop/s" << dec;
}
static bool lower_efficiency(const results_entry_t& e1, const results_entry_t& e2) {
return e1.default_efficiency < e2.default_efficiency;
}
virtual const char* invokation_name() const override { return "evaluate-defaults"; }
void show_usage_and_exit() const
{
cerr << "usage: " << invokation_name() << " default-sizes-data all-pot-sizes-data" << endl;
cerr << "checks how well the performance with default sizes compares to the best "
<< "performance measured over all POT sizes." << endl;
exit(1);
}
virtual void run(const vector<string>& input_filenames) const override
{
if (input_filenames.size() != 2) {
show_usage_and_exit();
}
inputfile_t inputfile_default_sizes(input_filenames[0]);
inputfile_t inputfile_all_pot_sizes(input_filenames[1]);
if (inputfile_default_sizes.type != inputfile_t::type_t::default_sizes) {
cerr << inputfile_default_sizes.filename << " is not an input file with default sizes." << endl;
show_usage_and_exit();
}
if (inputfile_all_pot_sizes.type != inputfile_t::type_t::all_pot_sizes) {
cerr << inputfile_all_pot_sizes.filename << " is not an input file with all POT sizes." << endl;
show_usage_and_exit();
}
vector<results_entry_t> results;
vector<results_entry_t> cubic_results;
uint16_t product_size = 0;
auto it_all_pot_sizes = inputfile_all_pot_sizes.entries.begin();
for (auto it_default_sizes = inputfile_default_sizes.entries.begin();
it_default_sizes != inputfile_default_sizes.entries.end();
++it_default_sizes)
{
if (it_default_sizes->product_size == product_size) {
continue;
}
product_size = it_default_sizes->product_size;
while (it_all_pot_sizes != inputfile_all_pot_sizes.entries.end() &&
it_all_pot_sizes->product_size != product_size)
{
++it_all_pot_sizes;
}
if (it_all_pot_sizes == inputfile_all_pot_sizes.entries.end()) {
break;
}
uint16_t best_pot_block_size = 0;
float best_pot_gflops = 0;
for (auto it = it_all_pot_sizes;
it != inputfile_all_pot_sizes.entries.end() && it->product_size == product_size;
++it)
{
if (it->gflops > best_pot_gflops) {
best_pot_gflops = it->gflops;
best_pot_block_size = it->pot_block_size;
}
}
results_entry_t entry;
entry.product_size = product_size;
entry.default_block_size = it_default_sizes->nonpot_block_size;
entry.best_pot_block_size = best_pot_block_size;
entry.default_gflops = it_default_sizes->gflops;
entry.best_pot_gflops = best_pot_gflops;
entry.default_efficiency = entry.default_gflops / entry.best_pot_gflops;
results.push_back(entry);
size_triple_t t(product_size);
if (t.k == t.m && t.m == t.n) {
cubic_results.push_back(entry);
}
}
cout << "All results:" << endl;
for (auto it = results.begin(); it != results.end(); ++it) {
cout << *it << endl;
}
cout << endl;
sort(results.begin(), results.end(), lower_efficiency);
const size_t n = min<size_t>(20, results.size());
cout << n << " worst results:" << endl;
for (size_t i = 0; i < n; i++) {
cout << results[i] << endl;
}
cout << endl;
cout << "cubic results:" << endl;
for (auto it = cubic_results.begin(); it != cubic_results.end(); ++it) {
cout << *it << endl;
}
cout << endl;
sort(cubic_results.begin(), cubic_results.end(), lower_efficiency);
cout.precision(2);
vector<float> a = {0.5f, 0.20f, 0.10f, 0.05f, 0.02f, 0.01f};
for (auto it = a.begin(); it != a.end(); ++it) {
size_t n = min(results.size() - 1, size_t(*it * results.size()));
cout << (100.0f * n / (results.size() - 1))
<< " % of product sizes have default efficiency <= "
<< 100.0f * results[n].default_efficiency << " %" << endl;
}
cout.precision(default_precision);
}
};
void show_usage_and_exit(int argc, char* argv[],
const vector<unique_ptr<action_t>>& available_actions)
{
cerr << "usage: " << argv[0] << " <action> [options...] <input files...>" << endl;
cerr << "available actions:" << endl;
for (auto it = available_actions.begin(); it != available_actions.end(); ++it) {
cerr << " " << (*it)->invokation_name() << endl;
}
cerr << "the input files should each contain an output of benchmark-blocking-sizes" << endl;
exit(1);
}
int main(int argc, char* argv[])
{
cout.precision(default_precision);
cerr.precision(default_precision);
vector<unique_ptr<action_t>> available_actions;
available_actions.emplace_back(new partition_action_t);
available_actions.emplace_back(new evaluate_defaults_action_t);
vector<string> input_filenames;
action_t* action = nullptr;
if (argc < 2) {
show_usage_and_exit(argc, argv, available_actions);
}
for (int i = 1; i < argc; i++) {
bool arg_handled = false;
// Step 1. Try to match action invokation names.
for (auto it = available_actions.begin(); it != available_actions.end(); ++it) {
if (!strcmp(argv[i], (*it)->invokation_name())) {
if (!action) {
action = it->get();
arg_handled = true;
break;
} else {
cerr << "can't specify more than one action!" << endl;
show_usage_and_exit(argc, argv, available_actions);
}
}
}
if (arg_handled) {
continue;
}
// Step 2. Try to match option names.
if (argv[i][0] == '-') {
if (!strcmp(argv[i], "--only-cubic-sizes")) {
only_cubic_sizes = true;
arg_handled = true;
}
if (!strcmp(argv[i], "--dump-tables")) {
dump_tables = true;
arg_handled = true;
}
if (!arg_handled) {
cerr << "Unrecognized option: " << argv[i] << endl;
show_usage_and_exit(argc, argv, available_actions);
}
}
if (arg_handled) {
continue;
}
// Step 3. Default to interpreting args as input filenames.
input_filenames.emplace_back(argv[i]);
}
if (dump_tables && only_cubic_sizes) {
cerr << "Incompatible options: --only-cubic-sizes and --dump-tables." << endl;
show_usage_and_exit(argc, argv, available_actions);
}
if (!action) {
show_usage_and_exit(argc, argv, available_actions);
}
action->run(input_filenames);
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/spmv.cpp | .cpp | 6,096 | 234 |
//g++-4.4 -DNOMTL -Wl,-rpath /usr/local/lib/oski -L /usr/local/lib/oski/ -l oski -l oski_util -l oski_util_Tid -DOSKI -I ~/Coding/LinearAlgebra/mtl4/ spmv.cpp -I .. -O2 -DNDEBUG -lrt -lm -l oski_mat_CSC_Tid -loskilt && ./a.out r200000 c200000 n100 t1 p1
#define SCALAR double
#include <iostream>
#include <algorithm>
#include "BenchTimer.h"
#include "BenchSparseUtil.h"
#define SPMV_BENCH(CODE) BENCH(t,tries,repeats,CODE);
// #ifdef MKL
//
// #include "mkl_types.h"
// #include "mkl_spblas.h"
//
// template<typename Lhs,typename Rhs,typename Res>
// void mkl_multiply(const Lhs& lhs, const Rhs& rhs, Res& res)
// {
// char n = 'N';
// float alpha = 1;
// char matdescra[6];
// matdescra[0] = 'G';
// matdescra[1] = 0;
// matdescra[2] = 0;
// matdescra[3] = 'C';
// mkl_scscmm(&n, lhs.rows(), rhs.cols(), lhs.cols(), &alpha, matdescra,
// lhs._valuePtr(), lhs._innerIndexPtr(), lhs.outerIndexPtr(),
// pntre, b, &ldb, &beta, c, &ldc);
// // mkl_somatcopy('C', 'T', lhs.rows(), lhs.cols(), 1,
// // lhs._valuePtr(), lhs.rows(), DST, dst_stride);
// }
//
// #endif
int main(int argc, char *argv[])
{
int size = 10000;
int rows = size;
int cols = size;
int nnzPerCol = 40;
int tries = 2;
int repeats = 2;
bool need_help = false;
for(int i = 1; i < argc; i++)
{
if(argv[i][0] == 'r')
{
rows = atoi(argv[i]+1);
}
else if(argv[i][0] == 'c')
{
cols = atoi(argv[i]+1);
}
else if(argv[i][0] == 'n')
{
nnzPerCol = atoi(argv[i]+1);
}
else if(argv[i][0] == 't')
{
tries = atoi(argv[i]+1);
}
else if(argv[i][0] == 'p')
{
repeats = atoi(argv[i]+1);
}
else
{
need_help = true;
}
}
if(need_help)
{
std::cout << argv[0] << " r<nb rows> c<nb columns> n<non zeros per column> t<nb tries> p<nb repeats>\n";
return 1;
}
std::cout << "SpMV " << rows << " x " << cols << " with " << nnzPerCol << " non zeros per column. (" << repeats << " repeats, and " << tries << " tries)\n\n";
EigenSparseMatrix sm(rows,cols);
DenseVector dv(cols), res(rows);
dv.setRandom();
BenchTimer t;
while (nnzPerCol>=4)
{
std::cout << "nnz: " << nnzPerCol << "\n";
sm.setZero();
fillMatrix2(nnzPerCol, rows, cols, sm);
// dense matrices
#ifdef DENSEMATRIX
{
DenseMatrix dm(rows,cols), (rows,cols);
eiToDense(sm, dm);
SPMV_BENCH(res = dm * sm);
std::cout << "Dense " << t.value()/repeats << "\t";
SPMV_BENCH(res = dm.transpose() * sm);
std::cout << t.value()/repeats << endl;
}
#endif
// eigen sparse matrices
{
SPMV_BENCH(res.noalias() += sm * dv; )
std::cout << "Eigen " << t.value()/repeats << "\t";
SPMV_BENCH(res.noalias() += sm.transpose() * dv; )
std::cout << t.value()/repeats << endl;
}
// CSparse
#ifdef CSPARSE
{
std::cout << "CSparse \n";
cs *csm;
eiToCSparse(sm, csm);
// BENCH();
// timer.stop();
// std::cout << " a * b:\t" << timer.value() << endl;
// BENCH( { m3 = cs_sorted_multiply2(m1, m2); cs_spfree(m3); } );
// std::cout << " a * b:\t" << timer.value() << endl;
}
#endif
#ifdef OSKI
{
oski_matrix_t om;
oski_vecview_t ov, ores;
oski_Init();
om = oski_CreateMatCSC(sm._outerIndexPtr(), sm._innerIndexPtr(), sm._valuePtr(), rows, cols,
SHARE_INPUTMAT, 1, INDEX_ZERO_BASED);
ov = oski_CreateVecView(dv.data(), cols, STRIDE_UNIT);
ores = oski_CreateVecView(res.data(), rows, STRIDE_UNIT);
SPMV_BENCH( oski_MatMult(om, OP_NORMAL, 1, ov, 0, ores) );
std::cout << "OSKI " << t.value()/repeats << "\t";
SPMV_BENCH( oski_MatMult(om, OP_TRANS, 1, ov, 0, ores) );
std::cout << t.value()/repeats << "\n";
// tune
t.reset();
t.start();
oski_SetHintMatMult(om, OP_NORMAL, 1.0, SYMBOLIC_VEC, 0.0, SYMBOLIC_VEC, ALWAYS_TUNE_AGGRESSIVELY);
oski_TuneMat(om);
t.stop();
double tuning = t.value();
SPMV_BENCH( oski_MatMult(om, OP_NORMAL, 1, ov, 0, ores) );
std::cout << "OSKI tuned " << t.value()/repeats << "\t";
SPMV_BENCH( oski_MatMult(om, OP_TRANS, 1, ov, 0, ores) );
std::cout << t.value()/repeats << "\t(" << tuning << ")\n";
oski_DestroyMat(om);
oski_DestroyVecView(ov);
oski_DestroyVecView(ores);
oski_Close();
}
#endif
#ifndef NOUBLAS
{
using namespace boost::numeric;
UblasMatrix um(rows,cols);
eiToUblas(sm, um);
boost::numeric::ublas::vector<Scalar> uv(cols), ures(rows);
Map<Matrix<Scalar,Dynamic,1> >(&uv[0], cols) = dv;
Map<Matrix<Scalar,Dynamic,1> >(&ures[0], rows) = res;
SPMV_BENCH(ublas::axpy_prod(um, uv, ures, true));
std::cout << "ublas " << t.value()/repeats << "\t";
SPMV_BENCH(ublas::axpy_prod(boost::numeric::ublas::trans(um), uv, ures, true));
std::cout << t.value()/repeats << endl;
}
#endif
// GMM++
#ifndef NOGMM
{
GmmSparse gm(rows,cols);
eiToGmm(sm, gm);
std::vector<Scalar> gv(cols), gres(rows);
Map<Matrix<Scalar,Dynamic,1> >(&gv[0], cols) = dv;
Map<Matrix<Scalar,Dynamic,1> >(&gres[0], rows) = res;
SPMV_BENCH(gmm::mult(gm, gv, gres));
std::cout << "GMM++ " << t.value()/repeats << "\t";
SPMV_BENCH(gmm::mult(gmm::transposed(gm), gv, gres));
std::cout << t.value()/repeats << endl;
}
#endif
// MTL4
#ifndef NOMTL
{
MtlSparse mm(rows,cols);
eiToMtl(sm, mm);
mtl::dense_vector<Scalar> mv(cols, 1.0);
mtl::dense_vector<Scalar> mres(rows, 1.0);
SPMV_BENCH(mres = mm * mv);
std::cout << "MTL4 " << t.value()/repeats << "\t";
SPMV_BENCH(mres = trans(mm) * mv);
std::cout << t.value()/repeats << endl;
}
#endif
std::cout << "\n";
if(nnzPerCol==1)
break;
nnzPerCol -= nnzPerCol/2;
}
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/benchGeometry.cpp | .cpp | 3,598 | 135 | #include <iostream>
#include <iomanip>
#include <Eigen/Core>
#include <Eigen/Geometry>
#include <bench/BenchTimer.h>
using namespace Eigen;
using namespace std;
#ifndef REPEAT
#define REPEAT 1000000
#endif
enum func_opt
{
TV,
TMATV,
TMATVMAT,
};
template <class res, class arg1, class arg2, int opt>
struct func;
template <class res, class arg1, class arg2>
struct func<res, arg1, arg2, TV>
{
static EIGEN_DONT_INLINE res run( arg1& a1, arg2& a2 )
{
asm ("");
return a1 * a2;
}
};
template <class res, class arg1, class arg2>
struct func<res, arg1, arg2, TMATV>
{
static EIGEN_DONT_INLINE res run( arg1& a1, arg2& a2 )
{
asm ("");
return a1.matrix() * a2;
}
};
template <class res, class arg1, class arg2>
struct func<res, arg1, arg2, TMATVMAT>
{
static EIGEN_DONT_INLINE res run( arg1& a1, arg2& a2 )
{
asm ("");
return res(a1.matrix() * a2.matrix());
}
};
template <class func, class arg1, class arg2>
struct test_transform
{
static void run()
{
arg1 a1;
a1.setIdentity();
arg2 a2;
a2.setIdentity();
BenchTimer timer;
timer.reset();
for (int k=0; k<10; ++k)
{
timer.start();
for (int k=0; k<REPEAT; ++k)
a2 = func::run( a1, a2 );
timer.stop();
}
cout << setprecision(4) << fixed << timer.value() << "s " << endl;;
}
};
#define run_vec( op, scalar, mode, option, vsize ) \
std::cout << #scalar << "\t " << #mode << "\t " << #option << " " << #vsize " "; \
{\
typedef Transform<scalar, 3, mode, option> Trans;\
typedef Matrix<scalar, vsize, 1, option> Vec;\
typedef func<Vec,Trans,Vec,op> Func;\
test_transform< Func, Trans, Vec >::run();\
}
#define run_trans( op, scalar, mode, option ) \
std::cout << #scalar << "\t " << #mode << "\t " << #option << " "; \
{\
typedef Transform<scalar, 3, mode, option> Trans;\
typedef func<Trans,Trans,Trans,op> Func;\
test_transform< Func, Trans, Trans >::run();\
}
int main(int argc, char* argv[])
{
cout << "vec = trans * vec" << endl;
run_vec(TV, float, Isometry, AutoAlign, 3);
run_vec(TV, float, Isometry, DontAlign, 3);
run_vec(TV, float, Isometry, AutoAlign, 4);
run_vec(TV, float, Isometry, DontAlign, 4);
run_vec(TV, float, Projective, AutoAlign, 4);
run_vec(TV, float, Projective, DontAlign, 4);
run_vec(TV, double, Isometry, AutoAlign, 3);
run_vec(TV, double, Isometry, DontAlign, 3);
run_vec(TV, double, Isometry, AutoAlign, 4);
run_vec(TV, double, Isometry, DontAlign, 4);
run_vec(TV, double, Projective, AutoAlign, 4);
run_vec(TV, double, Projective, DontAlign, 4);
cout << "vec = trans.matrix() * vec" << endl;
run_vec(TMATV, float, Isometry, AutoAlign, 4);
run_vec(TMATV, float, Isometry, DontAlign, 4);
run_vec(TMATV, double, Isometry, AutoAlign, 4);
run_vec(TMATV, double, Isometry, DontAlign, 4);
cout << "trans = trans1 * trans" << endl;
run_trans(TV, float, Isometry, AutoAlign);
run_trans(TV, float, Isometry, DontAlign);
run_trans(TV, double, Isometry, AutoAlign);
run_trans(TV, double, Isometry, DontAlign);
run_trans(TV, float, Projective, AutoAlign);
run_trans(TV, float, Projective, DontAlign);
run_trans(TV, double, Projective, AutoAlign);
run_trans(TV, double, Projective, DontAlign);
cout << "trans = trans1.matrix() * trans.matrix()" << endl;
run_trans(TMATVMAT, float, Isometry, AutoAlign);
run_trans(TMATVMAT, float, Isometry, DontAlign);
run_trans(TMATVMAT, double, Isometry, AutoAlign);
run_trans(TMATVMAT, double, Isometry, DontAlign);
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/bench_reverse.cpp | .cpp | 2,159 | 85 |
#include <iostream>
#include <Eigen/Core>
#include <bench/BenchUtil.h>
using namespace Eigen;
#ifndef REPEAT
#define REPEAT 100000
#endif
#ifndef TRIES
#define TRIES 20
#endif
typedef double Scalar;
template <typename MatrixType>
__attribute__ ((noinline)) void bench_reverse(const MatrixType& m)
{
int rows = m.rows();
int cols = m.cols();
int size = m.size();
int repeats = (REPEAT*1000)/size;
MatrixType a = MatrixType::Random(rows,cols);
MatrixType b = MatrixType::Random(rows,cols);
BenchTimer timerB, timerH, timerV;
Scalar acc = 0;
int r = internal::random<int>(0,rows-1);
int c = internal::random<int>(0,cols-1);
for (int t=0; t<TRIES; ++t)
{
timerB.start();
for (int k=0; k<repeats; ++k)
{
asm("#begin foo");
b = a.reverse();
asm("#end foo");
acc += b.coeff(r,c);
}
timerB.stop();
}
if (MatrixType::RowsAtCompileTime==Dynamic)
std::cout << "dyn ";
else
std::cout << "fixed ";
std::cout << rows << " x " << cols << " \t"
<< (timerB.value() * REPEAT) / repeats << "s "
<< "(" << 1e-6 * size*repeats/timerB.value() << " MFLOPS)\t";
std::cout << "\n";
// make sure the compiler does not optimize too much
if (acc==123)
std::cout << acc;
}
int main(int argc, char* argv[])
{
const int dynsizes[] = {4,6,8,16,24,32,49,64,128,256,512,900,0};
std::cout << "size no sqrt standard";
// #ifdef BENCH_GSL
// std::cout << " GSL (standard + double + ATLAS) ";
// #endif
std::cout << "\n";
for (uint i=0; dynsizes[i]>0; ++i)
{
bench_reverse(Matrix<Scalar,Dynamic,Dynamic>(dynsizes[i],dynsizes[i]));
bench_reverse(Matrix<Scalar,Dynamic,1>(dynsizes[i]*dynsizes[i]));
}
// bench_reverse(Matrix<Scalar,2,2>());
// bench_reverse(Matrix<Scalar,3,3>());
// bench_reverse(Matrix<Scalar,4,4>());
// bench_reverse(Matrix<Scalar,5,5>());
// bench_reverse(Matrix<Scalar,6,6>());
// bench_reverse(Matrix<Scalar,7,7>());
// bench_reverse(Matrix<Scalar,8,8>());
// bench_reverse(Matrix<Scalar,12,12>());
// bench_reverse(Matrix<Scalar,16,16>());
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/benchEigenSolver.cpp | .cpp | 5,788 | 213 |
// g++ -DNDEBUG -O3 -I.. benchEigenSolver.cpp -o benchEigenSolver && ./benchEigenSolver
// options:
// -DBENCH_GMM
// -DBENCH_GSL -lgsl /usr/lib/libcblas.so.3
// -DEIGEN_DONT_VECTORIZE
// -msse2
// -DREPEAT=100
// -DTRIES=10
// -DSCALAR=double
#include <iostream>
#include <Eigen/Core>
#include <Eigen/QR>
#include <bench/BenchUtil.h>
using namespace Eigen;
#ifndef REPEAT
#define REPEAT 1000
#endif
#ifndef TRIES
#define TRIES 4
#endif
#ifndef SCALAR
#define SCALAR float
#endif
typedef SCALAR Scalar;
template <typename MatrixType>
__attribute__ ((noinline)) void benchEigenSolver(const MatrixType& m)
{
int rows = m.rows();
int cols = m.cols();
int stdRepeats = std::max(1,int((REPEAT*1000)/(rows*rows*sqrt(rows))));
int saRepeats = stdRepeats * 4;
typedef typename MatrixType::Scalar Scalar;
typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> SquareMatrixType;
MatrixType a = MatrixType::Random(rows,cols);
SquareMatrixType covMat = a * a.adjoint();
BenchTimer timerSa, timerStd;
Scalar acc = 0;
int r = internal::random<int>(0,covMat.rows()-1);
int c = internal::random<int>(0,covMat.cols()-1);
{
SelfAdjointEigenSolver<SquareMatrixType> ei(covMat);
for (int t=0; t<TRIES; ++t)
{
timerSa.start();
for (int k=0; k<saRepeats; ++k)
{
ei.compute(covMat);
acc += ei.eigenvectors().coeff(r,c);
}
timerSa.stop();
}
}
{
EigenSolver<SquareMatrixType> ei(covMat);
for (int t=0; t<TRIES; ++t)
{
timerStd.start();
for (int k=0; k<stdRepeats; ++k)
{
ei.compute(covMat);
acc += ei.eigenvectors().coeff(r,c);
}
timerStd.stop();
}
}
if (MatrixType::RowsAtCompileTime==Dynamic)
std::cout << "dyn ";
else
std::cout << "fixed ";
std::cout << covMat.rows() << " \t"
<< timerSa.value() * REPEAT / saRepeats << "s \t"
<< timerStd.value() * REPEAT / stdRepeats << "s";
#ifdef BENCH_GMM
if (MatrixType::RowsAtCompileTime==Dynamic)
{
timerSa.reset();
timerStd.reset();
gmm::dense_matrix<Scalar> gmmCovMat(covMat.rows(),covMat.cols());
gmm::dense_matrix<Scalar> eigvect(covMat.rows(),covMat.cols());
std::vector<Scalar> eigval(covMat.rows());
eiToGmm(covMat, gmmCovMat);
for (int t=0; t<TRIES; ++t)
{
timerSa.start();
for (int k=0; k<saRepeats; ++k)
{
gmm::symmetric_qr_algorithm(gmmCovMat, eigval, eigvect);
acc += eigvect(r,c);
}
timerSa.stop();
}
// the non-selfadjoint solver does not compute the eigen vectors
// for (int t=0; t<TRIES; ++t)
// {
// timerStd.start();
// for (int k=0; k<stdRepeats; ++k)
// {
// gmm::implicit_qr_algorithm(gmmCovMat, eigval, eigvect);
// acc += eigvect(r,c);
// }
// timerStd.stop();
// }
std::cout << " | \t"
<< timerSa.value() * REPEAT / saRepeats << "s"
<< /*timerStd.value() * REPEAT / stdRepeats << "s"*/ " na ";
}
#endif
#ifdef BENCH_GSL
if (MatrixType::RowsAtCompileTime==Dynamic)
{
timerSa.reset();
timerStd.reset();
gsl_matrix* gslCovMat = gsl_matrix_alloc(covMat.rows(),covMat.cols());
gsl_matrix* gslCopy = gsl_matrix_alloc(covMat.rows(),covMat.cols());
gsl_matrix* eigvect = gsl_matrix_alloc(covMat.rows(),covMat.cols());
gsl_vector* eigval = gsl_vector_alloc(covMat.rows());
gsl_eigen_symmv_workspace* eisymm = gsl_eigen_symmv_alloc(covMat.rows());
gsl_matrix_complex* eigvectz = gsl_matrix_complex_alloc(covMat.rows(),covMat.cols());
gsl_vector_complex* eigvalz = gsl_vector_complex_alloc(covMat.rows());
gsl_eigen_nonsymmv_workspace* einonsymm = gsl_eigen_nonsymmv_alloc(covMat.rows());
eiToGsl(covMat, &gslCovMat);
for (int t=0; t<TRIES; ++t)
{
timerSa.start();
for (int k=0; k<saRepeats; ++k)
{
gsl_matrix_memcpy(gslCopy,gslCovMat);
gsl_eigen_symmv(gslCopy, eigval, eigvect, eisymm);
acc += gsl_matrix_get(eigvect,r,c);
}
timerSa.stop();
}
for (int t=0; t<TRIES; ++t)
{
timerStd.start();
for (int k=0; k<stdRepeats; ++k)
{
gsl_matrix_memcpy(gslCopy,gslCovMat);
gsl_eigen_nonsymmv(gslCopy, eigvalz, eigvectz, einonsymm);
acc += GSL_REAL(gsl_matrix_complex_get(eigvectz,r,c));
}
timerStd.stop();
}
std::cout << " | \t"
<< timerSa.value() * REPEAT / saRepeats << "s \t"
<< timerStd.value() * REPEAT / stdRepeats << "s";
gsl_matrix_free(gslCovMat);
gsl_vector_free(gslCopy);
gsl_matrix_free(eigvect);
gsl_vector_free(eigval);
gsl_matrix_complex_free(eigvectz);
gsl_vector_complex_free(eigvalz);
gsl_eigen_symmv_free(eisymm);
gsl_eigen_nonsymmv_free(einonsymm);
}
#endif
std::cout << "\n";
// make sure the compiler does not optimize too much
if (acc==123)
std::cout << acc;
}
int main(int argc, char* argv[])
{
const int dynsizes[] = {4,6,8,12,16,24,32,64,128,256,512,0};
std::cout << "size selfadjoint generic";
#ifdef BENCH_GMM
std::cout << " GMM++ ";
#endif
#ifdef BENCH_GSL
std::cout << " GSL (double + ATLAS) ";
#endif
std::cout << "\n";
for (uint i=0; dynsizes[i]>0; ++i)
benchEigenSolver(Matrix<Scalar,Dynamic,Dynamic>(dynsizes[i],dynsizes[i]));
benchEigenSolver(Matrix<Scalar,2,2>());
benchEigenSolver(Matrix<Scalar,3,3>());
benchEigenSolver(Matrix<Scalar,4,4>());
benchEigenSolver(Matrix<Scalar,6,6>());
benchEigenSolver(Matrix<Scalar,8,8>());
benchEigenSolver(Matrix<Scalar,12,12>());
benchEigenSolver(Matrix<Scalar,16,16>());
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/basicbenchmark.cpp | .cpp | 1,107 | 36 |
#include <iostream>
#include "BenchUtil.h"
#include "basicbenchmark.h"
int main(int argc, char *argv[])
{
DISABLE_SSE_EXCEPTIONS();
// this is the list of matrix type and size we want to bench:
// ((suffix) (matrix size) (number of iterations))
#define MODES ((3d)(3)(4000000)) ((4d)(4)(1000000)) ((Xd)(4)(1000000)) ((Xd)(20)(10000))
// #define MODES ((Xd)(20)(10000))
#define _GENERATE_HEADER(R,ARG,EL) << BOOST_PP_STRINGIZE(BOOST_PP_SEQ_HEAD(EL)) << "-" \
<< BOOST_PP_STRINGIZE(BOOST_PP_SEQ_ELEM(1,EL)) << "x" \
<< BOOST_PP_STRINGIZE(BOOST_PP_SEQ_ELEM(1,EL)) << " / "
std::cout BOOST_PP_SEQ_FOR_EACH(_GENERATE_HEADER, ~, MODES ) << endl;
const int tries = 10;
#define _RUN_BENCH(R,ARG,EL) \
std::cout << ARG( \
BOOST_PP_CAT(Matrix, BOOST_PP_SEQ_HEAD(EL)) (\
BOOST_PP_SEQ_ELEM(1,EL),BOOST_PP_SEQ_ELEM(1,EL)), BOOST_PP_SEQ_ELEM(2,EL), tries) \
<< " ";
BOOST_PP_SEQ_FOR_EACH(_RUN_BENCH, benchBasic<LazyEval>, MODES );
std::cout << endl;
BOOST_PP_SEQ_FOR_EACH(_RUN_BENCH, benchBasic<EarlyEval>, MODES );
std::cout << endl;
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/benchmarkX.cpp | .cpp | 640 | 37 | // g++ -fopenmp -I .. -O3 -DNDEBUG -finline-limit=1000 benchmarkX.cpp -o b && time ./b
#include <iostream>
#include <Eigen/Core>
using namespace std;
using namespace Eigen;
#ifndef MATTYPE
#define MATTYPE MatrixXLd
#endif
#ifndef MATSIZE
#define MATSIZE 400
#endif
#ifndef REPEAT
#define REPEAT 100
#endif
int main(int argc, char *argv[])
{
MATTYPE I = MATTYPE::Ones(MATSIZE,MATSIZE);
MATTYPE m(MATSIZE,MATSIZE);
for(int i = 0; i < MATSIZE; i++) for(int j = 0; j < MATSIZE; j++)
{
m(i,j) = (i+j+1)/(MATSIZE*MATSIZE);
}
for(int a = 0; a < REPEAT; a++)
{
m = I + 0.0001 * (m + m*m);
}
cout << m(0,0) << endl;
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/sparse_cholesky.cpp | .cpp | 6,260 | 217 | // #define EIGEN_TAUCS_SUPPORT
// #define EIGEN_CHOLMOD_SUPPORT
#include <iostream>
#include <Eigen/Sparse>
// g++ -DSIZE=10000 -DDENSITY=0.001 sparse_cholesky.cpp -I.. -DDENSEMATRI -O3 -g0 -DNDEBUG -DNBTRIES=1 -I /home/gael/Coding/LinearAlgebra/taucs_full/src/ -I/home/gael/Coding/LinearAlgebra/taucs_full/build/linux/ -L/home/gael/Coding/LinearAlgebra/taucs_full/lib/linux/ -ltaucs /home/gael/Coding/LinearAlgebra/GotoBLAS/libgoto.a -lpthread -I /home/gael/Coding/LinearAlgebra/SuiteSparse/CHOLMOD/Include/ $CHOLLIB -I /home/gael/Coding/LinearAlgebra/SuiteSparse/UFconfig/ /home/gael/Coding/LinearAlgebra/SuiteSparse/CCOLAMD/Lib/libccolamd.a /home/gael/Coding/LinearAlgebra/SuiteSparse/CHOLMOD/Lib/libcholmod.a -lmetis /home/gael/Coding/LinearAlgebra/SuiteSparse/AMD/Lib/libamd.a /home/gael/Coding/LinearAlgebra/SuiteSparse/CAMD/Lib/libcamd.a /home/gael/Coding/LinearAlgebra/SuiteSparse/CCOLAMD/Lib/libccolamd.a /home/gael/Coding/LinearAlgebra/SuiteSparse/COLAMD/Lib/libcolamd.a -llapack && ./a.out
#define NOGMM
#define NOMTL
#ifndef SIZE
#define SIZE 10
#endif
#ifndef DENSITY
#define DENSITY 0.01
#endif
#ifndef REPEAT
#define REPEAT 1
#endif
#include "BenchSparseUtil.h"
#ifndef MINDENSITY
#define MINDENSITY 0.0004
#endif
#ifndef NBTRIES
#define NBTRIES 10
#endif
#define BENCH(X) \
timer.reset(); \
for (int _j=0; _j<NBTRIES; ++_j) { \
timer.start(); \
for (int _k=0; _k<REPEAT; ++_k) { \
X \
} timer.stop(); }
// typedef SparseMatrix<Scalar,UpperTriangular> EigenSparseTriMatrix;
typedef SparseMatrix<Scalar,SelfAdjoint|LowerTriangular> EigenSparseSelfAdjointMatrix;
void fillSpdMatrix(float density, int rows, int cols, EigenSparseSelfAdjointMatrix& dst)
{
dst.startFill(rows*cols*density);
for(int j = 0; j < cols; j++)
{
dst.fill(j,j) = internal::random<Scalar>(10,20);
for(int i = j+1; i < rows; i++)
{
Scalar v = (internal::random<float>(0,1) < density) ? internal::random<Scalar>() : 0;
if (v!=0)
dst.fill(i,j) = v;
}
}
dst.endFill();
}
#include <Eigen/Cholesky>
template<int Backend>
void doEigen(const char* name, const EigenSparseSelfAdjointMatrix& sm1, int flags = 0)
{
std::cout << name << "..." << std::flush;
BenchTimer timer;
timer.start();
SparseLLT<EigenSparseSelfAdjointMatrix,Backend> chol(sm1, flags);
timer.stop();
std::cout << ":\t" << timer.value() << endl;
std::cout << " nnz: " << sm1.nonZeros() << " => " << chol.matrixL().nonZeros() << "\n";
// std::cout << "sparse\n" << chol.matrixL() << "%\n";
}
int main(int argc, char *argv[])
{
int rows = SIZE;
int cols = SIZE;
float density = DENSITY;
BenchTimer timer;
VectorXf b = VectorXf::Random(cols);
VectorXf x = VectorXf::Random(cols);
bool densedone = false;
//for (float density = DENSITY; density>=MINDENSITY; density*=0.5)
// float density = 0.5;
{
EigenSparseSelfAdjointMatrix sm1(rows, cols);
std::cout << "Generate sparse matrix (might take a while)...\n";
fillSpdMatrix(density, rows, cols, sm1);
std::cout << "DONE\n\n";
// dense matrices
#ifdef DENSEMATRIX
if (!densedone)
{
densedone = true;
std::cout << "Eigen Dense\t" << density*100 << "%\n";
DenseMatrix m1(rows,cols);
eiToDense(sm1, m1);
m1 = (m1 + m1.transpose()).eval();
m1.diagonal() *= 0.5;
// BENCH(LLT<DenseMatrix> chol(m1);)
// std::cout << "dense:\t" << timer.value() << endl;
BenchTimer timer;
timer.start();
LLT<DenseMatrix> chol(m1);
timer.stop();
std::cout << "dense:\t" << timer.value() << endl;
int count = 0;
for (int j=0; j<cols; ++j)
for (int i=j; i<rows; ++i)
if (!internal::isMuchSmallerThan(internal::abs(chol.matrixL()(i,j)), 0.1))
count++;
std::cout << "dense: " << "nnz = " << count << "\n";
// std::cout << "dense:\n" << m1 << "\n\n" << chol.matrixL() << endl;
}
#endif
// eigen sparse matrices
doEigen<Eigen::DefaultBackend>("Eigen/Sparse", sm1, Eigen::IncompleteFactorization);
#ifdef EIGEN_CHOLMOD_SUPPORT
doEigen<Eigen::Cholmod>("Eigen/Cholmod", sm1, Eigen::IncompleteFactorization);
#endif
#ifdef EIGEN_TAUCS_SUPPORT
doEigen<Eigen::Taucs>("Eigen/Taucs", sm1, Eigen::IncompleteFactorization);
#endif
#if 0
// TAUCS
{
taucs_ccs_matrix A = sm1.asTaucsMatrix();
//BENCH(taucs_ccs_matrix* chol = taucs_ccs_factor_llt(&A, 0, 0);)
// BENCH(taucs_supernodal_factor_to_ccs(taucs_ccs_factor_llt_ll(&A));)
// std::cout << "taucs:\t" << timer.value() << endl;
taucs_ccs_matrix* chol = taucs_ccs_factor_llt(&A, 0, 0);
for (int j=0; j<cols; ++j)
{
for (int i=chol->colptr[j]; i<chol->colptr[j+1]; ++i)
std::cout << chol->values.d[i] << " ";
}
}
// CHOLMOD
#ifdef EIGEN_CHOLMOD_SUPPORT
{
cholmod_common c;
cholmod_start (&c);
cholmod_sparse A;
cholmod_factor *L;
A = sm1.asCholmodMatrix();
BenchTimer timer;
// timer.reset();
timer.start();
std::vector<int> perm(cols);
// std::vector<int> set(ncols);
for (int i=0; i<cols; ++i)
perm[i] = i;
// c.nmethods = 1;
// c.method[0] = 1;
c.nmethods = 1;
c.method [0].ordering = CHOLMOD_NATURAL;
c.postorder = 0;
c.final_ll = 1;
L = cholmod_analyze_p(&A, &perm[0], &perm[0], cols, &c);
timer.stop();
std::cout << "cholmod/analyze:\t" << timer.value() << endl;
timer.reset();
timer.start();
cholmod_factorize(&A, L, &c);
timer.stop();
std::cout << "cholmod/factorize:\t" << timer.value() << endl;
cholmod_sparse* cholmat = cholmod_factor_to_sparse(L, &c);
cholmod_print_factor(L, "Factors", &c);
cholmod_print_sparse(cholmat, "Chol", &c);
cholmod_write_sparse(stdout, cholmat, 0, 0, &c);
//
// cholmod_print_sparse(&A, "A", &c);
// cholmod_write_sparse(stdout, &A, 0, 0, &c);
// for (int j=0; j<cols; ++j)
// {
// for (int i=chol->colptr[j]; i<chol->colptr[j+1]; ++i)
// std::cout << chol->values.s[i] << " ";
// }
}
#endif
#endif
}
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/benchCholesky.cpp | .cpp | 3,534 | 143 |
// g++ -DNDEBUG -O3 -I.. benchLLT.cpp -o benchLLT && ./benchLLT
// options:
// -DBENCH_GSL -lgsl /usr/lib/libcblas.so.3
// -DEIGEN_DONT_VECTORIZE
// -msse2
// -DREPEAT=100
// -DTRIES=10
// -DSCALAR=double
#include <iostream>
#include <Eigen/Core>
#include <Eigen/Cholesky>
#include <bench/BenchUtil.h>
using namespace Eigen;
#ifndef REPEAT
#define REPEAT 10000
#endif
#ifndef TRIES
#define TRIES 10
#endif
typedef float Scalar;
template <typename MatrixType>
__attribute__ ((noinline)) void benchLLT(const MatrixType& m)
{
int rows = m.rows();
int cols = m.cols();
double cost = 0;
for (int j=0; j<rows; ++j)
{
int r = std::max(rows - j -1,0);
cost += 2*(r*j+r+j);
}
int repeats = (REPEAT*1000)/(rows*rows);
typedef typename MatrixType::Scalar Scalar;
typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> SquareMatrixType;
MatrixType a = MatrixType::Random(rows,cols);
SquareMatrixType covMat = a * a.adjoint();
BenchTimer timerNoSqrt, timerSqrt;
Scalar acc = 0;
int r = internal::random<int>(0,covMat.rows()-1);
int c = internal::random<int>(0,covMat.cols()-1);
for (int t=0; t<TRIES; ++t)
{
timerNoSqrt.start();
for (int k=0; k<repeats; ++k)
{
LDLT<SquareMatrixType> cholnosqrt(covMat);
acc += cholnosqrt.matrixL().coeff(r,c);
}
timerNoSqrt.stop();
}
for (int t=0; t<TRIES; ++t)
{
timerSqrt.start();
for (int k=0; k<repeats; ++k)
{
LLT<SquareMatrixType> chol(covMat);
acc += chol.matrixL().coeff(r,c);
}
timerSqrt.stop();
}
if (MatrixType::RowsAtCompileTime==Dynamic)
std::cout << "dyn ";
else
std::cout << "fixed ";
std::cout << covMat.rows() << " \t"
<< (timerNoSqrt.best()) / repeats << "s "
<< "(" << 1e-9 * cost*repeats/timerNoSqrt.best() << " GFLOPS)\t"
<< (timerSqrt.best()) / repeats << "s "
<< "(" << 1e-9 * cost*repeats/timerSqrt.best() << " GFLOPS)\n";
#ifdef BENCH_GSL
if (MatrixType::RowsAtCompileTime==Dynamic)
{
timerSqrt.reset();
gsl_matrix* gslCovMat = gsl_matrix_alloc(covMat.rows(),covMat.cols());
gsl_matrix* gslCopy = gsl_matrix_alloc(covMat.rows(),covMat.cols());
eiToGsl(covMat, &gslCovMat);
for (int t=0; t<TRIES; ++t)
{
timerSqrt.start();
for (int k=0; k<repeats; ++k)
{
gsl_matrix_memcpy(gslCopy,gslCovMat);
gsl_linalg_cholesky_decomp(gslCopy);
acc += gsl_matrix_get(gslCopy,r,c);
}
timerSqrt.stop();
}
std::cout << " | \t"
<< timerSqrt.value() * REPEAT / repeats << "s";
gsl_matrix_free(gslCovMat);
}
#endif
std::cout << "\n";
// make sure the compiler does not optimize too much
if (acc==123)
std::cout << acc;
}
int main(int argc, char* argv[])
{
const int dynsizes[] = {4,6,8,16,24,32,49,64,128,256,512,900,1500,0};
std::cout << "size LDLT LLT";
// #ifdef BENCH_GSL
// std::cout << " GSL (standard + double + ATLAS) ";
// #endif
std::cout << "\n";
for (int i=0; dynsizes[i]>0; ++i)
benchLLT(Matrix<Scalar,Dynamic,Dynamic>(dynsizes[i],dynsizes[i]));
benchLLT(Matrix<Scalar,2,2>());
benchLLT(Matrix<Scalar,3,3>());
benchLLT(Matrix<Scalar,4,4>());
benchLLT(Matrix<Scalar,5,5>());
benchLLT(Matrix<Scalar,6,6>());
benchLLT(Matrix<Scalar,7,7>());
benchLLT(Matrix<Scalar,8,8>());
benchLLT(Matrix<Scalar,12,12>());
benchLLT(Matrix<Scalar,16,16>());
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/sparse_product.cpp | .cpp | 8,999 | 324 |
//g++ -O3 -g0 -DNDEBUG sparse_product.cpp -I.. -I/home/gael/Coding/LinearAlgebra/mtl4/ -DDENSITY=0.005 -DSIZE=10000 && ./a.out
//g++ -O3 -g0 -DNDEBUG sparse_product.cpp -I.. -I/home/gael/Coding/LinearAlgebra/mtl4/ -DDENSITY=0.05 -DSIZE=2000 && ./a.out
// -DNOGMM -DNOMTL -DCSPARSE
// -I /home/gael/Coding/LinearAlgebra/CSparse/Include/ /home/gael/Coding/LinearAlgebra/CSparse/Lib/libcsparse.a
#include <typeinfo>
#ifndef SIZE
#define SIZE 1000000
#endif
#ifndef NNZPERCOL
#define NNZPERCOL 6
#endif
#ifndef REPEAT
#define REPEAT 1
#endif
#include <algorithm>
#include "BenchTimer.h"
#include "BenchUtil.h"
#include "BenchSparseUtil.h"
#ifndef NBTRIES
#define NBTRIES 1
#endif
#define BENCH(X) \
timer.reset(); \
for (int _j=0; _j<NBTRIES; ++_j) { \
timer.start(); \
for (int _k=0; _k<REPEAT; ++_k) { \
X \
} timer.stop(); }
// #ifdef MKL
//
// #include "mkl_types.h"
// #include "mkl_spblas.h"
//
// template<typename Lhs,typename Rhs,typename Res>
// void mkl_multiply(const Lhs& lhs, const Rhs& rhs, Res& res)
// {
// char n = 'N';
// float alpha = 1;
// char matdescra[6];
// matdescra[0] = 'G';
// matdescra[1] = 0;
// matdescra[2] = 0;
// matdescra[3] = 'C';
// mkl_scscmm(&n, lhs.rows(), rhs.cols(), lhs.cols(), &alpha, matdescra,
// lhs._valuePtr(), lhs._innerIndexPtr(), lhs.outerIndexPtr(),
// pntre, b, &ldb, &beta, c, &ldc);
// // mkl_somatcopy('C', 'T', lhs.rows(), lhs.cols(), 1,
// // lhs._valuePtr(), lhs.rows(), DST, dst_stride);
// }
//
// #endif
#ifdef CSPARSE
cs* cs_sorted_multiply(const cs* a, const cs* b)
{
// return cs_multiply(a,b);
cs* A = cs_transpose(a, 1);
cs* B = cs_transpose(b, 1);
cs* D = cs_multiply(B,A); /* D = B'*A' */
cs_spfree (A) ;
cs_spfree (B) ;
cs_dropzeros (D) ; /* drop zeros from D */
cs* C = cs_transpose (D, 1) ; /* C = D', so that C is sorted */
cs_spfree (D) ;
return C;
// cs* A = cs_transpose(a, 1);
// cs* C = cs_transpose(A, 1);
// return C;
}
cs* cs_sorted_multiply2(const cs* a, const cs* b)
{
cs* D = cs_multiply(a,b);
cs* E = cs_transpose(D,1);
cs_spfree(D);
cs* C = cs_transpose(E,1);
cs_spfree(E);
return C;
}
#endif
void bench_sort();
int main(int argc, char *argv[])
{
// bench_sort();
int rows = SIZE;
int cols = SIZE;
float density = DENSITY;
EigenSparseMatrix sm1(rows,cols), sm2(rows,cols), sm3(rows,cols), sm4(rows,cols);
BenchTimer timer;
for (int nnzPerCol = NNZPERCOL; nnzPerCol>1; nnzPerCol/=1.1)
{
sm1.setZero();
sm2.setZero();
fillMatrix2(nnzPerCol, rows, cols, sm1);
fillMatrix2(nnzPerCol, rows, cols, sm2);
// std::cerr << "filling OK\n";
// dense matrices
#ifdef DENSEMATRIX
{
std::cout << "Eigen Dense\t" << nnzPerCol << "%\n";
DenseMatrix m1(rows,cols), m2(rows,cols), m3(rows,cols);
eiToDense(sm1, m1);
eiToDense(sm2, m2);
timer.reset();
timer.start();
for (int k=0; k<REPEAT; ++k)
m3 = m1 * m2;
timer.stop();
std::cout << " a * b:\t" << timer.value() << endl;
timer.reset();
timer.start();
for (int k=0; k<REPEAT; ++k)
m3 = m1.transpose() * m2;
timer.stop();
std::cout << " a' * b:\t" << timer.value() << endl;
timer.reset();
timer.start();
for (int k=0; k<REPEAT; ++k)
m3 = m1.transpose() * m2.transpose();
timer.stop();
std::cout << " a' * b':\t" << timer.value() << endl;
timer.reset();
timer.start();
for (int k=0; k<REPEAT; ++k)
m3 = m1 * m2.transpose();
timer.stop();
std::cout << " a * b':\t" << timer.value() << endl;
}
#endif
// eigen sparse matrices
{
std::cout << "Eigen sparse\t" << sm1.nonZeros()/(float(sm1.rows())*float(sm1.cols()))*100 << "% * "
<< sm2.nonZeros()/(float(sm2.rows())*float(sm2.cols()))*100 << "%\n";
BENCH(sm3 = sm1 * sm2; )
std::cout << " a * b:\t" << timer.value() << endl;
// BENCH(sm3 = sm1.transpose() * sm2; )
// std::cout << " a' * b:\t" << timer.value() << endl;
// //
// BENCH(sm3 = sm1.transpose() * sm2.transpose(); )
// std::cout << " a' * b':\t" << timer.value() << endl;
// //
// BENCH(sm3 = sm1 * sm2.transpose(); )
// std::cout << " a * b' :\t" << timer.value() << endl;
// std::cout << "\n";
//
// BENCH( sm3._experimentalNewProduct(sm1, sm2); )
// std::cout << " a * b:\t" << timer.value() << endl;
//
// BENCH(sm3._experimentalNewProduct(sm1.transpose(),sm2); )
// std::cout << " a' * b:\t" << timer.value() << endl;
// //
// BENCH(sm3._experimentalNewProduct(sm1.transpose(),sm2.transpose()); )
// std::cout << " a' * b':\t" << timer.value() << endl;
// //
// BENCH(sm3._experimentalNewProduct(sm1, sm2.transpose());)
// std::cout << " a * b' :\t" << timer.value() << endl;
}
// eigen dyn-sparse matrices
/*{
DynamicSparseMatrix<Scalar> m1(sm1), m2(sm2), m3(sm3);
std::cout << "Eigen dyn-sparse\t" << m1.nonZeros()/(float(m1.rows())*float(m1.cols()))*100 << "% * "
<< m2.nonZeros()/(float(m2.rows())*float(m2.cols()))*100 << "%\n";
// timer.reset();
// timer.start();
BENCH(for (int k=0; k<REPEAT; ++k) m3 = m1 * m2;)
// timer.stop();
std::cout << " a * b:\t" << timer.value() << endl;
// std::cout << sm3 << "\n";
timer.reset();
timer.start();
// std::cerr << "transpose...\n";
// EigenSparseMatrix sm4 = sm1.transpose();
// std::cout << sm4.nonZeros() << " == " << sm1.nonZeros() << "\n";
// exit(1);
// std::cerr << "transpose OK\n";
// std::cout << sm1 << "\n\n" << sm1.transpose() << "\n\n" << sm4.transpose() << "\n\n";
BENCH(for (int k=0; k<REPEAT; ++k) m3 = m1.transpose() * m2;)
// timer.stop();
std::cout << " a' * b:\t" << timer.value() << endl;
// timer.reset();
// timer.start();
BENCH( for (int k=0; k<REPEAT; ++k) m3 = m1.transpose() * m2.transpose(); )
// timer.stop();
std::cout << " a' * b':\t" << timer.value() << endl;
// timer.reset();
// timer.start();
BENCH( for (int k=0; k<REPEAT; ++k) m3 = m1 * m2.transpose(); )
// timer.stop();
std::cout << " a * b' :\t" << timer.value() << endl;
}*/
// CSparse
#ifdef CSPARSE
{
std::cout << "CSparse \t" << nnzPerCol << "%\n";
cs *m1, *m2, *m3;
eiToCSparse(sm1, m1);
eiToCSparse(sm2, m2);
BENCH(
{
m3 = cs_sorted_multiply(m1, m2);
if (!m3)
{
std::cerr << "cs_multiply failed\n";
}
// cs_print(m3, 0);
cs_spfree(m3);
}
);
// timer.stop();
std::cout << " a * b:\t" << timer.value() << endl;
// BENCH( { m3 = cs_sorted_multiply2(m1, m2); cs_spfree(m3); } );
// std::cout << " a * b:\t" << timer.value() << endl;
}
#endif
#ifndef NOUBLAS
{
std::cout << "ublas\t" << nnzPerCol << "%\n";
UBlasSparse m1(rows,cols), m2(rows,cols), m3(rows,cols);
eiToUblas(sm1, m1);
eiToUblas(sm2, m2);
BENCH(boost::numeric::ublas::prod(m1, m2, m3););
std::cout << " a * b:\t" << timer.value() << endl;
}
#endif
// GMM++
#ifndef NOGMM
{
std::cout << "GMM++ sparse\t" << nnzPerCol << "%\n";
GmmDynSparse gmmT3(rows,cols);
GmmSparse m1(rows,cols), m2(rows,cols), m3(rows,cols);
eiToGmm(sm1, m1);
eiToGmm(sm2, m2);
BENCH(gmm::mult(m1, m2, gmmT3););
std::cout << " a * b:\t" << timer.value() << endl;
// BENCH(gmm::mult(gmm::transposed(m1), m2, gmmT3););
// std::cout << " a' * b:\t" << timer.value() << endl;
//
// if (rows<500)
// {
// BENCH(gmm::mult(gmm::transposed(m1), gmm::transposed(m2), gmmT3););
// std::cout << " a' * b':\t" << timer.value() << endl;
//
// BENCH(gmm::mult(m1, gmm::transposed(m2), gmmT3););
// std::cout << " a * b':\t" << timer.value() << endl;
// }
// else
// {
// std::cout << " a' * b':\t" << "forever" << endl;
// std::cout << " a * b':\t" << "forever" << endl;
// }
}
#endif
// MTL4
#ifndef NOMTL
{
std::cout << "MTL4\t" << nnzPerCol << "%\n";
MtlSparse m1(rows,cols), m2(rows,cols), m3(rows,cols);
eiToMtl(sm1, m1);
eiToMtl(sm2, m2);
BENCH(m3 = m1 * m2;);
std::cout << " a * b:\t" << timer.value() << endl;
// BENCH(m3 = trans(m1) * m2;);
// std::cout << " a' * b:\t" << timer.value() << endl;
//
// BENCH(m3 = trans(m1) * trans(m2););
// std::cout << " a' * b':\t" << timer.value() << endl;
//
// BENCH(m3 = m1 * trans(m2););
// std::cout << " a * b' :\t" << timer.value() << endl;
}
#endif
std::cout << "\n\n";
}
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/dense_solvers.cpp | .cpp | 6,416 | 187 | #include <iostream>
#include "BenchTimer.h"
#include <Eigen/Dense>
#include <map>
#include <vector>
#include <string>
#include <sstream>
using namespace Eigen;
std::map<std::string,Array<float,1,8,DontAlign|RowMajor> > results;
std::vector<std::string> labels;
std::vector<Array2i> sizes;
template<typename Solver,typename MatrixType>
EIGEN_DONT_INLINE
void compute_norm_equation(Solver &solver, const MatrixType &A) {
if(A.rows()!=A.cols())
solver.compute(A.transpose()*A);
else
solver.compute(A);
}
template<typename Solver,typename MatrixType>
EIGEN_DONT_INLINE
void compute(Solver &solver, const MatrixType &A) {
solver.compute(A);
}
template<typename Scalar,int Size>
void bench(int id, int rows, int size = Size)
{
typedef Matrix<Scalar,Dynamic,Size> Mat;
typedef Matrix<Scalar,Dynamic,Dynamic> MatDyn;
typedef Matrix<Scalar,Size,Size> MatSquare;
Mat A(rows,size);
A.setRandom();
if(rows==size)
A = A*A.adjoint();
BenchTimer t_llt, t_ldlt, t_lu, t_fplu, t_qr, t_cpqr, t_cod, t_fpqr, t_jsvd, t_bdcsvd;
int svd_opt = ComputeThinU|ComputeThinV;
int tries = 5;
int rep = 1000/size;
if(rep==0) rep = 1;
// rep = rep*rep;
LLT<MatSquare> llt(size);
LDLT<MatSquare> ldlt(size);
PartialPivLU<MatSquare> lu(size);
FullPivLU<MatSquare> fplu(size,size);
HouseholderQR<Mat> qr(A.rows(),A.cols());
ColPivHouseholderQR<Mat> cpqr(A.rows(),A.cols());
CompleteOrthogonalDecomposition<Mat> cod(A.rows(),A.cols());
FullPivHouseholderQR<Mat> fpqr(A.rows(),A.cols());
JacobiSVD<MatDyn> jsvd(A.rows(),A.cols());
BDCSVD<MatDyn> bdcsvd(A.rows(),A.cols());
BENCH(t_llt, tries, rep, compute_norm_equation(llt,A));
BENCH(t_ldlt, tries, rep, compute_norm_equation(ldlt,A));
BENCH(t_lu, tries, rep, compute_norm_equation(lu,A));
if(size<=1000)
BENCH(t_fplu, tries, rep, compute_norm_equation(fplu,A));
BENCH(t_qr, tries, rep, compute(qr,A));
BENCH(t_cpqr, tries, rep, compute(cpqr,A));
BENCH(t_cod, tries, rep, compute(cod,A));
if(size*rows<=10000000)
BENCH(t_fpqr, tries, rep, compute(fpqr,A));
if(size<500) // JacobiSVD is really too slow for too large matrices
BENCH(t_jsvd, tries, rep, jsvd.compute(A,svd_opt));
// if(size*rows<=20000000)
BENCH(t_bdcsvd, tries, rep, bdcsvd.compute(A,svd_opt));
results["LLT"][id] = t_llt.best();
results["LDLT"][id] = t_ldlt.best();
results["PartialPivLU"][id] = t_lu.best();
results["FullPivLU"][id] = t_fplu.best();
results["HouseholderQR"][id] = t_qr.best();
results["ColPivHouseholderQR"][id] = t_cpqr.best();
results["CompleteOrthogonalDecomposition"][id] = t_cod.best();
results["FullPivHouseholderQR"][id] = t_fpqr.best();
results["JacobiSVD"][id] = t_jsvd.best();
results["BDCSVD"][id] = t_bdcsvd.best();
}
int main()
{
labels.push_back("LLT");
labels.push_back("LDLT");
labels.push_back("PartialPivLU");
labels.push_back("FullPivLU");
labels.push_back("HouseholderQR");
labels.push_back("ColPivHouseholderQR");
labels.push_back("CompleteOrthogonalDecomposition");
labels.push_back("FullPivHouseholderQR");
labels.push_back("JacobiSVD");
labels.push_back("BDCSVD");
for(int i=0; i<labels.size(); ++i)
results[labels[i]].fill(-1);
const int small = 8;
sizes.push_back(Array2i(small,small));
sizes.push_back(Array2i(100,100));
sizes.push_back(Array2i(1000,1000));
sizes.push_back(Array2i(4000,4000));
sizes.push_back(Array2i(10000,small));
sizes.push_back(Array2i(10000,100));
sizes.push_back(Array2i(10000,1000));
sizes.push_back(Array2i(10000,4000));
using namespace std;
for(int k=0; k<sizes.size(); ++k)
{
cout << sizes[k](0) << "x" << sizes[k](1) << "...\n";
bench<float,Dynamic>(k,sizes[k](0),sizes[k](1));
}
cout.width(32);
cout << "solver/size";
cout << " ";
for(int k=0; k<sizes.size(); ++k)
{
std::stringstream ss;
ss << sizes[k](0) << "x" << sizes[k](1);
cout.width(10); cout << ss.str(); cout << " ";
}
cout << endl;
for(int i=0; i<labels.size(); ++i)
{
cout.width(32); cout << labels[i]; cout << " ";
ArrayXf r = (results[labels[i]]*100000.f).floor()/100.f;
for(int k=0; k<sizes.size(); ++k)
{
cout.width(10);
if(r(k)>=1e6) cout << "-";
else cout << r(k);
cout << " ";
}
cout << endl;
}
// HTML output
cout << "<table class=\"manual\">" << endl;
cout << "<tr><th>solver/size</th>" << endl;
for(int k=0; k<sizes.size(); ++k)
cout << " <th>" << sizes[k](0) << "x" << sizes[k](1) << "</th>";
cout << "</tr>" << endl;
for(int i=0; i<labels.size(); ++i)
{
cout << "<tr";
if(i%2==1) cout << " class=\"alt\"";
cout << "><td>" << labels[i] << "</td>";
ArrayXf r = (results[labels[i]]*100000.f).floor()/100.f;
for(int k=0; k<sizes.size(); ++k)
{
if(r(k)>=1e6) cout << "<td>-</td>";
else
{
cout << "<td>" << r(k);
if(i>0)
cout << " (x" << numext::round(10.f*results[labels[i]](k)/results["LLT"](k))/10.f << ")";
if(i<4 && sizes[k](0)!=sizes[k](1))
cout << " <sup><a href=\"#note_ls\">*</a></sup>";
cout << "</td>";
}
}
cout << "</tr>" << endl;
}
cout << "</table>" << endl;
// cout << "LLT (ms) " << (results["LLT"]*1000.).format(fmt) << "\n";
// cout << "LDLT (%) " << (results["LDLT"]/results["LLT"]).format(fmt) << "\n";
// cout << "PartialPivLU (%) " << (results["PartialPivLU"]/results["LLT"]).format(fmt) << "\n";
// cout << "FullPivLU (%) " << (results["FullPivLU"]/results["LLT"]).format(fmt) << "\n";
// cout << "HouseholderQR (%) " << (results["HouseholderQR"]/results["LLT"]).format(fmt) << "\n";
// cout << "ColPivHouseholderQR (%) " << (results["ColPivHouseholderQR"]/results["LLT"]).format(fmt) << "\n";
// cout << "CompleteOrthogonalDecomposition (%) " << (results["CompleteOrthogonalDecomposition"]/results["LLT"]).format(fmt) << "\n";
// cout << "FullPivHouseholderQR (%) " << (results["FullPivHouseholderQR"]/results["LLT"]).format(fmt) << "\n";
// cout << "JacobiSVD (%) " << (results["JacobiSVD"]/results["LLT"]).format(fmt) << "\n";
// cout << "BDCSVD (%) " << (results["BDCSVD"]/results["LLT"]).format(fmt) << "\n";
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/benchVecAdd.cpp | .cpp | 5,193 | 136 |
#include <iostream>
#include <Eigen/Core>
#include <bench/BenchTimer.h>
using namespace Eigen;
#ifndef SIZE
#define SIZE 50
#endif
#ifndef REPEAT
#define REPEAT 10000
#endif
typedef float Scalar;
__attribute__ ((noinline)) void benchVec(Scalar* a, Scalar* b, Scalar* c, int size);
__attribute__ ((noinline)) void benchVec(MatrixXf& a, MatrixXf& b, MatrixXf& c);
__attribute__ ((noinline)) void benchVec(VectorXf& a, VectorXf& b, VectorXf& c);
int main(int argc, char* argv[])
{
int size = SIZE * 8;
int size2 = size * size;
Scalar* a = internal::aligned_new<Scalar>(size2);
Scalar* b = internal::aligned_new<Scalar>(size2+4)+1;
Scalar* c = internal::aligned_new<Scalar>(size2);
for (int i=0; i<size; ++i)
{
a[i] = b[i] = c[i] = 0;
}
BenchTimer timer;
timer.reset();
for (int k=0; k<10; ++k)
{
timer.start();
benchVec(a, b, c, size2);
timer.stop();
}
std::cout << timer.value() << "s " << (double(size2*REPEAT)/timer.value())/(1024.*1024.*1024.) << " GFlops\n";
return 0;
for (int innersize = size; innersize>2 ; --innersize)
{
if (size2%innersize==0)
{
int outersize = size2/innersize;
MatrixXf ma = Map<MatrixXf>(a, innersize, outersize );
MatrixXf mb = Map<MatrixXf>(b, innersize, outersize );
MatrixXf mc = Map<MatrixXf>(c, innersize, outersize );
timer.reset();
for (int k=0; k<3; ++k)
{
timer.start();
benchVec(ma, mb, mc);
timer.stop();
}
std::cout << innersize << " x " << outersize << " " << timer.value() << "s " << (double(size2*REPEAT)/timer.value())/(1024.*1024.*1024.) << " GFlops\n";
}
}
VectorXf va = Map<VectorXf>(a, size2);
VectorXf vb = Map<VectorXf>(b, size2);
VectorXf vc = Map<VectorXf>(c, size2);
timer.reset();
for (int k=0; k<3; ++k)
{
timer.start();
benchVec(va, vb, vc);
timer.stop();
}
std::cout << timer.value() << "s " << (double(size2*REPEAT)/timer.value())/(1024.*1024.*1024.) << " GFlops\n";
return 0;
}
void benchVec(MatrixXf& a, MatrixXf& b, MatrixXf& c)
{
for (int k=0; k<REPEAT; ++k)
a = a + b;
}
void benchVec(VectorXf& a, VectorXf& b, VectorXf& c)
{
for (int k=0; k<REPEAT; ++k)
a = a + b;
}
void benchVec(Scalar* a, Scalar* b, Scalar* c, int size)
{
typedef internal::packet_traits<Scalar>::type PacketScalar;
const int PacketSize = internal::packet_traits<Scalar>::size;
PacketScalar a0, a1, a2, a3, b0, b1, b2, b3;
for (int k=0; k<REPEAT; ++k)
for (int i=0; i<size; i+=PacketSize*8)
{
// a0 = internal::pload(&a[i]);
// b0 = internal::pload(&b[i]);
// a1 = internal::pload(&a[i+1*PacketSize]);
// b1 = internal::pload(&b[i+1*PacketSize]);
// a2 = internal::pload(&a[i+2*PacketSize]);
// b2 = internal::pload(&b[i+2*PacketSize]);
// a3 = internal::pload(&a[i+3*PacketSize]);
// b3 = internal::pload(&b[i+3*PacketSize]);
// internal::pstore(&a[i], internal::padd(a0, b0));
// a0 = internal::pload(&a[i+4*PacketSize]);
// b0 = internal::pload(&b[i+4*PacketSize]);
//
// internal::pstore(&a[i+1*PacketSize], internal::padd(a1, b1));
// a1 = internal::pload(&a[i+5*PacketSize]);
// b1 = internal::pload(&b[i+5*PacketSize]);
//
// internal::pstore(&a[i+2*PacketSize], internal::padd(a2, b2));
// a2 = internal::pload(&a[i+6*PacketSize]);
// b2 = internal::pload(&b[i+6*PacketSize]);
//
// internal::pstore(&a[i+3*PacketSize], internal::padd(a3, b3));
// a3 = internal::pload(&a[i+7*PacketSize]);
// b3 = internal::pload(&b[i+7*PacketSize]);
//
// internal::pstore(&a[i+4*PacketSize], internal::padd(a0, b0));
// internal::pstore(&a[i+5*PacketSize], internal::padd(a1, b1));
// internal::pstore(&a[i+6*PacketSize], internal::padd(a2, b2));
// internal::pstore(&a[i+7*PacketSize], internal::padd(a3, b3));
internal::pstore(&a[i+2*PacketSize], internal::padd(internal::ploadu(&a[i+2*PacketSize]), internal::ploadu(&b[i+2*PacketSize])));
internal::pstore(&a[i+3*PacketSize], internal::padd(internal::ploadu(&a[i+3*PacketSize]), internal::ploadu(&b[i+3*PacketSize])));
internal::pstore(&a[i+4*PacketSize], internal::padd(internal::ploadu(&a[i+4*PacketSize]), internal::ploadu(&b[i+4*PacketSize])));
internal::pstore(&a[i+5*PacketSize], internal::padd(internal::ploadu(&a[i+5*PacketSize]), internal::ploadu(&b[i+5*PacketSize])));
internal::pstore(&a[i+6*PacketSize], internal::padd(internal::ploadu(&a[i+6*PacketSize]), internal::ploadu(&b[i+6*PacketSize])));
internal::pstore(&a[i+7*PacketSize], internal::padd(internal::ploadu(&a[i+7*PacketSize]), internal::ploadu(&b[i+7*PacketSize])));
}
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/product_threshold.cpp | .cpp | 3,232 | 144 |
#include <iostream>
#include <Eigen/Core>
#include <bench/BenchTimer.h>
using namespace Eigen;
using namespace std;
#define END 9
template<int S> struct map_size { enum { ret = S }; };
template<> struct map_size<10> { enum { ret = 20 }; };
template<> struct map_size<11> { enum { ret = 50 }; };
template<> struct map_size<12> { enum { ret = 100 }; };
template<> struct map_size<13> { enum { ret = 300 }; };
template<int M, int N,int K> struct alt_prod
{
enum {
ret = M==1 && N==1 ? InnerProduct
: K==1 ? OuterProduct
: M==1 ? GemvProduct
: N==1 ? GemvProduct
: GemmProduct
};
};
void print_mode(int mode)
{
if(mode==InnerProduct) std::cout << "i";
if(mode==OuterProduct) std::cout << "o";
if(mode==CoeffBasedProductMode) std::cout << "c";
if(mode==LazyCoeffBasedProductMode) std::cout << "l";
if(mode==GemvProduct) std::cout << "v";
if(mode==GemmProduct) std::cout << "m";
}
template<int Mode, typename Lhs, typename Rhs, typename Res>
EIGEN_DONT_INLINE void prod(const Lhs& a, const Rhs& b, Res& c)
{
c.noalias() += typename ProductReturnType<Lhs,Rhs,Mode>::Type(a,b);
}
template<int M, int N, int K, typename Scalar, int Mode>
EIGEN_DONT_INLINE void bench_prod()
{
typedef Matrix<Scalar,M,K> Lhs; Lhs a; a.setRandom();
typedef Matrix<Scalar,K,N> Rhs; Rhs b; b.setRandom();
typedef Matrix<Scalar,M,N> Res; Res c; c.setRandom();
BenchTimer t;
double n = 2.*double(M)*double(N)*double(K);
int rep = 100000./n;
rep /= 2;
if(rep<1) rep = 1;
do {
rep *= 2;
t.reset();
BENCH(t,1,rep,prod<CoeffBasedProductMode>(a,b,c));
} while(t.best()<0.1);
t.reset();
BENCH(t,5,rep,prod<Mode>(a,b,c));
print_mode(Mode);
std::cout << int(1e-6*n*rep/t.best()) << "\t";
}
template<int N> struct print_n;
template<int M, int N, int K> struct loop_on_m;
template<int M, int N, int K, typename Scalar, int Mode> struct loop_on_n;
template<int M, int N, int K>
struct loop_on_k
{
static void run()
{
std::cout << "K=" << K << "\t";
print_n<N>::run();
std::cout << "\n";
loop_on_m<M,N,K>::run();
std::cout << "\n\n";
loop_on_k<M,N,K+1>::run();
}
};
template<int M, int N>
struct loop_on_k<M,N,END> { static void run(){} };
template<int M, int N, int K>
struct loop_on_m
{
static void run()
{
std::cout << M << "f\t";
loop_on_n<M,N,K,float,CoeffBasedProductMode>::run();
std::cout << "\n";
std::cout << M << "f\t";
loop_on_n<M,N,K,float,-1>::run();
std::cout << "\n";
loop_on_m<M+1,N,K>::run();
}
};
template<int N, int K>
struct loop_on_m<END,N,K> { static void run(){} };
template<int M, int N, int K, typename Scalar, int Mode>
struct loop_on_n
{
static void run()
{
bench_prod<M,N,K,Scalar,Mode==-1? alt_prod<M,N,K>::ret : Mode>();
loop_on_n<M,N+1,K,Scalar,Mode>::run();
}
};
template<int M, int K, typename Scalar, int Mode>
struct loop_on_n<M,END,K,Scalar,Mode> { static void run(){} };
template<int N> struct print_n
{
static void run()
{
std::cout << map_size<N>::ret << "\t";
print_n<N+1>::run();
}
};
template<> struct print_n<END> { static void run(){} };
int main()
{
loop_on_k<1,1,1>::run();
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/check_cache_queries.cpp | .cpp | 3,269 | 102 |
#define EIGEN_INTERNAL_DEBUG_CACHE_QUERY
#include <iostream>
#include "../Eigen/Core"
using namespace Eigen;
using namespace std;
#define DUMP_CPUID(CODE) {\
int abcd[4]; \
abcd[0] = abcd[1] = abcd[2] = abcd[3] = 0;\
EIGEN_CPUID(abcd, CODE, 0); \
std::cout << "The code " << CODE << " gives " \
<< (int*)(abcd[0]) << " " << (int*)(abcd[1]) << " " \
<< (int*)(abcd[2]) << " " << (int*)(abcd[3]) << " " << std::endl; \
}
int main()
{
cout << "Eigen's L1 = " << internal::queryL1CacheSize() << endl;
cout << "Eigen's L2/L3 = " << internal::queryTopLevelCacheSize() << endl;
int l1, l2, l3;
internal::queryCacheSizes(l1, l2, l3);
cout << "Eigen's L1, L2, L3 = " << l1 << " " << l2 << " " << l3 << endl;
#ifdef EIGEN_CPUID
int abcd[4];
int string[8];
char* string_char = (char*)(string);
// vendor ID
EIGEN_CPUID(abcd,0x0,0);
string[0] = abcd[1];
string[1] = abcd[3];
string[2] = abcd[2];
string[3] = 0;
cout << endl;
cout << "vendor id = " << string_char << endl;
cout << endl;
int max_funcs = abcd[0];
internal::queryCacheSizes_intel_codes(l1, l2, l3);
cout << "Eigen's intel codes L1, L2, L3 = " << l1 << " " << l2 << " " << l3 << endl;
if(max_funcs>=4)
{
internal::queryCacheSizes_intel_direct(l1, l2, l3);
cout << "Eigen's intel direct L1, L2, L3 = " << l1 << " " << l2 << " " << l3 << endl;
}
internal::queryCacheSizes_amd(l1, l2, l3);
cout << "Eigen's amd L1, L2, L3 = " << l1 << " " << l2 << " " << l3 << endl;
cout << endl;
// dump Intel direct method
if(max_funcs>=4)
{
l1 = l2 = l3 = 0;
int cache_id = 0;
int cache_type = 0;
do {
abcd[0] = abcd[1] = abcd[2] = abcd[3] = 0;
EIGEN_CPUID(abcd,0x4,cache_id);
cache_type = (abcd[0] & 0x0F) >> 0;
int cache_level = (abcd[0] & 0xE0) >> 5; // A[7:5]
int ways = (abcd[1] & 0xFFC00000) >> 22; // B[31:22]
int partitions = (abcd[1] & 0x003FF000) >> 12; // B[21:12]
int line_size = (abcd[1] & 0x00000FFF) >> 0; // B[11:0]
int sets = (abcd[2]); // C[31:0]
int cache_size = (ways+1) * (partitions+1) * (line_size+1) * (sets+1);
cout << "cache[" << cache_id << "].type = " << cache_type << "\n";
cout << "cache[" << cache_id << "].level = " << cache_level << "\n";
cout << "cache[" << cache_id << "].ways = " << ways << "\n";
cout << "cache[" << cache_id << "].partitions = " << partitions << "\n";
cout << "cache[" << cache_id << "].line_size = " << line_size << "\n";
cout << "cache[" << cache_id << "].sets = " << sets << "\n";
cout << "cache[" << cache_id << "].size = " << cache_size << "\n";
cache_id++;
} while(cache_type>0 && cache_id<16);
}
// dump everything
std::cout << endl <<"Raw dump:" << endl;
for(int i=0; i<max_funcs; ++i)
DUMP_CPUID(i);
DUMP_CPUID(0x80000000);
DUMP_CPUID(0x80000001);
DUMP_CPUID(0x80000002);
DUMP_CPUID(0x80000003);
DUMP_CPUID(0x80000004);
DUMP_CPUID(0x80000005);
DUMP_CPUID(0x80000006);
DUMP_CPUID(0x80000007);
DUMP_CPUID(0x80000008);
#else
cout << "EIGEN_CPUID is not defined" << endl;
#endif
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/sparse_lu.cpp | .cpp | 3,011 | 133 |
// g++ -I.. sparse_lu.cpp -O3 -g0 -I /usr/include/superlu/ -lsuperlu -lgfortran -DSIZE=1000 -DDENSITY=.05 && ./a.out
#define EIGEN_SUPERLU_SUPPORT
#define EIGEN_UMFPACK_SUPPORT
#include <Eigen/Sparse>
#define NOGMM
#define NOMTL
#ifndef SIZE
#define SIZE 10
#endif
#ifndef DENSITY
#define DENSITY 0.01
#endif
#ifndef REPEAT
#define REPEAT 1
#endif
#include "BenchSparseUtil.h"
#ifndef MINDENSITY
#define MINDENSITY 0.0004
#endif
#ifndef NBTRIES
#define NBTRIES 10
#endif
#define BENCH(X) \
timer.reset(); \
for (int _j=0; _j<NBTRIES; ++_j) { \
timer.start(); \
for (int _k=0; _k<REPEAT; ++_k) { \
X \
} timer.stop(); }
typedef Matrix<Scalar,Dynamic,1> VectorX;
#include <Eigen/LU>
template<int Backend>
void doEigen(const char* name, const EigenSparseMatrix& sm1, const VectorX& b, VectorX& x, int flags = 0)
{
std::cout << name << "..." << std::flush;
BenchTimer timer; timer.start();
SparseLU<EigenSparseMatrix,Backend> lu(sm1, flags);
timer.stop();
if (lu.succeeded())
std::cout << ":\t" << timer.value() << endl;
else
{
std::cout << ":\t FAILED" << endl;
return;
}
bool ok;
timer.reset(); timer.start();
ok = lu.solve(b,&x);
timer.stop();
if (ok)
std::cout << " solve:\t" << timer.value() << endl;
else
std::cout << " solve:\t" << " FAILED" << endl;
//std::cout << x.transpose() << "\n";
}
int main(int argc, char *argv[])
{
int rows = SIZE;
int cols = SIZE;
float density = DENSITY;
BenchTimer timer;
VectorX b = VectorX::Random(cols);
VectorX x = VectorX::Random(cols);
bool densedone = false;
//for (float density = DENSITY; density>=MINDENSITY; density*=0.5)
// float density = 0.5;
{
EigenSparseMatrix sm1(rows, cols);
fillMatrix(density, rows, cols, sm1);
// dense matrices
#ifdef DENSEMATRIX
if (!densedone)
{
densedone = true;
std::cout << "Eigen Dense\t" << density*100 << "%\n";
DenseMatrix m1(rows,cols);
eiToDense(sm1, m1);
BenchTimer timer;
timer.start();
FullPivLU<DenseMatrix> lu(m1);
timer.stop();
std::cout << "Eigen/dense:\t" << timer.value() << endl;
timer.reset();
timer.start();
lu.solve(b,&x);
timer.stop();
std::cout << " solve:\t" << timer.value() << endl;
// std::cout << b.transpose() << "\n";
// std::cout << x.transpose() << "\n";
}
#endif
#ifdef EIGEN_UMFPACK_SUPPORT
x.setZero();
doEigen<Eigen::UmfPack>("Eigen/UmfPack (auto)", sm1, b, x, 0);
#endif
#ifdef EIGEN_SUPERLU_SUPPORT
x.setZero();
doEigen<Eigen::SuperLU>("Eigen/SuperLU (nat)", sm1, b, x, Eigen::NaturalOrdering);
// doEigen<Eigen::SuperLU>("Eigen/SuperLU (MD AT+A)", sm1, b, x, Eigen::MinimumDegree_AT_PLUS_A);
// doEigen<Eigen::SuperLU>("Eigen/SuperLU (MD ATA)", sm1, b, x, Eigen::MinimumDegree_ATA);
doEigen<Eigen::SuperLU>("Eigen/SuperLU (COLAMD)", sm1, b, x, Eigen::ColApproxMinimumDegree);
#endif
}
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/bench_norm.cpp | .cpp | 11,652 | 361 | #include <typeinfo>
#include <iostream>
#include <Eigen/Core>
#include "BenchTimer.h"
using namespace Eigen;
using namespace std;
template<typename T>
EIGEN_DONT_INLINE typename T::Scalar sqsumNorm(T& v)
{
return v.norm();
}
template<typename T>
EIGEN_DONT_INLINE typename T::Scalar stableNorm(T& v)
{
return v.stableNorm();
}
template<typename T>
EIGEN_DONT_INLINE typename T::Scalar hypotNorm(T& v)
{
return v.hypotNorm();
}
template<typename T>
EIGEN_DONT_INLINE typename T::Scalar blueNorm(T& v)
{
return v.blueNorm();
}
template<typename T>
EIGEN_DONT_INLINE typename T::Scalar lapackNorm(T& v)
{
typedef typename T::Scalar Scalar;
int n = v.size();
Scalar scale = 0;
Scalar ssq = 1;
for (int i=0;i<n;++i)
{
Scalar ax = std::abs(v.coeff(i));
if (scale >= ax)
{
ssq += numext::abs2(ax/scale);
}
else
{
ssq = Scalar(1) + ssq * numext::abs2(scale/ax);
scale = ax;
}
}
return scale * std::sqrt(ssq);
}
template<typename T>
EIGEN_DONT_INLINE typename T::Scalar twopassNorm(T& v)
{
typedef typename T::Scalar Scalar;
Scalar s = v.array().abs().maxCoeff();
return s*(v/s).norm();
}
template<typename T>
EIGEN_DONT_INLINE typename T::Scalar bl2passNorm(T& v)
{
return v.stableNorm();
}
template<typename T>
EIGEN_DONT_INLINE typename T::Scalar divacNorm(T& v)
{
int n =v.size() / 2;
for (int i=0;i<n;++i)
v(i) = v(2*i)*v(2*i) + v(2*i+1)*v(2*i+1);
n = n/2;
while (n>0)
{
for (int i=0;i<n;++i)
v(i) = v(2*i) + v(2*i+1);
n = n/2;
}
return std::sqrt(v(0));
}
namespace Eigen {
namespace internal {
#ifdef EIGEN_VECTORIZE
Packet4f plt(const Packet4f& a, Packet4f& b) { return _mm_cmplt_ps(a,b); }
Packet2d plt(const Packet2d& a, Packet2d& b) { return _mm_cmplt_pd(a,b); }
Packet4f pandnot(const Packet4f& a, Packet4f& b) { return _mm_andnot_ps(a,b); }
Packet2d pandnot(const Packet2d& a, Packet2d& b) { return _mm_andnot_pd(a,b); }
#endif
}
}
template<typename T>
EIGEN_DONT_INLINE typename T::Scalar pblueNorm(const T& v)
{
#ifndef EIGEN_VECTORIZE
return v.blueNorm();
#else
typedef typename T::Scalar Scalar;
static int nmax = 0;
static Scalar b1, b2, s1m, s2m, overfl, rbig, relerr;
int n;
if(nmax <= 0)
{
int nbig, ibeta, it, iemin, iemax, iexp;
Scalar abig, eps;
nbig = std::numeric_limits<int>::max(); // largest integer
ibeta = std::numeric_limits<Scalar>::radix; //NumTraits<Scalar>::Base; // base for floating-point numbers
it = std::numeric_limits<Scalar>::digits; //NumTraits<Scalar>::Mantissa; // number of base-beta digits in mantissa
iemin = std::numeric_limits<Scalar>::min_exponent; // minimum exponent
iemax = std::numeric_limits<Scalar>::max_exponent; // maximum exponent
rbig = std::numeric_limits<Scalar>::max(); // largest floating-point number
// Check the basic machine-dependent constants.
if(iemin > 1 - 2*it || 1+it>iemax || (it==2 && ibeta<5)
|| (it<=4 && ibeta <= 3 ) || it<2)
{
eigen_assert(false && "the algorithm cannot be guaranteed on this computer");
}
iexp = -((1-iemin)/2);
b1 = std::pow(ibeta, iexp); // lower boundary of midrange
iexp = (iemax + 1 - it)/2;
b2 = std::pow(ibeta,iexp); // upper boundary of midrange
iexp = (2-iemin)/2;
s1m = std::pow(ibeta,iexp); // scaling factor for lower range
iexp = - ((iemax+it)/2);
s2m = std::pow(ibeta,iexp); // scaling factor for upper range
overfl = rbig*s2m; // overfow boundary for abig
eps = std::pow(ibeta, 1-it);
relerr = std::sqrt(eps); // tolerance for neglecting asml
abig = 1.0/eps - 1.0;
if (Scalar(nbig)>abig) nmax = abig; // largest safe n
else nmax = nbig;
}
typedef typename internal::packet_traits<Scalar>::type Packet;
const int ps = internal::packet_traits<Scalar>::size;
Packet pasml = internal::pset1<Packet>(Scalar(0));
Packet pamed = internal::pset1<Packet>(Scalar(0));
Packet pabig = internal::pset1<Packet>(Scalar(0));
Packet ps2m = internal::pset1<Packet>(s2m);
Packet ps1m = internal::pset1<Packet>(s1m);
Packet pb2 = internal::pset1<Packet>(b2);
Packet pb1 = internal::pset1<Packet>(b1);
for(int j=0; j<v.size(); j+=ps)
{
Packet ax = internal::pabs(v.template packet<Aligned>(j));
Packet ax_s2m = internal::pmul(ax,ps2m);
Packet ax_s1m = internal::pmul(ax,ps1m);
Packet maskBig = internal::plt(pb2,ax);
Packet maskSml = internal::plt(ax,pb1);
// Packet maskMed = internal::pand(maskSml,maskBig);
// Packet scale = internal::pset1(Scalar(0));
// scale = internal::por(scale, internal::pand(maskBig,ps2m));
// scale = internal::por(scale, internal::pand(maskSml,ps1m));
// scale = internal::por(scale, internal::pandnot(internal::pset1(Scalar(1)),maskMed));
// ax = internal::pmul(ax,scale);
// ax = internal::pmul(ax,ax);
// pabig = internal::padd(pabig, internal::pand(maskBig, ax));
// pasml = internal::padd(pasml, internal::pand(maskSml, ax));
// pamed = internal::padd(pamed, internal::pandnot(ax,maskMed));
pabig = internal::padd(pabig, internal::pand(maskBig, internal::pmul(ax_s2m,ax_s2m)));
pasml = internal::padd(pasml, internal::pand(maskSml, internal::pmul(ax_s1m,ax_s1m)));
pamed = internal::padd(pamed, internal::pandnot(internal::pmul(ax,ax),internal::pand(maskSml,maskBig)));
}
Scalar abig = internal::predux(pabig);
Scalar asml = internal::predux(pasml);
Scalar amed = internal::predux(pamed);
if(abig > Scalar(0))
{
abig = std::sqrt(abig);
if(abig > overfl)
{
eigen_assert(false && "overflow");
return rbig;
}
if(amed > Scalar(0))
{
abig = abig/s2m;
amed = std::sqrt(amed);
}
else
{
return abig/s2m;
}
}
else if(asml > Scalar(0))
{
if (amed > Scalar(0))
{
abig = std::sqrt(amed);
amed = std::sqrt(asml) / s1m;
}
else
{
return std::sqrt(asml)/s1m;
}
}
else
{
return std::sqrt(amed);
}
asml = std::min(abig, amed);
abig = std::max(abig, amed);
if(asml <= abig*relerr)
return abig;
else
return abig * std::sqrt(Scalar(1) + numext::abs2(asml/abig));
#endif
}
#define BENCH_PERF(NRM) { \
float af = 0; double ad = 0; std::complex<float> ac = 0; \
Eigen::BenchTimer tf, td, tcf; tf.reset(); td.reset(); tcf.reset();\
for (int k=0; k<tries; ++k) { \
tf.start(); \
for (int i=0; i<iters; ++i) { af += NRM(vf); } \
tf.stop(); \
} \
for (int k=0; k<tries; ++k) { \
td.start(); \
for (int i=0; i<iters; ++i) { ad += NRM(vd); } \
td.stop(); \
} \
/*for (int k=0; k<std::max(1,tries/3); ++k) { \
tcf.start(); \
for (int i=0; i<iters; ++i) { ac += NRM(vcf); } \
tcf.stop(); \
} */\
std::cout << #NRM << "\t" << tf.value() << " " << td.value() << " " << tcf.value() << "\n"; \
}
void check_accuracy(double basef, double based, int s)
{
double yf = basef * std::abs(internal::random<double>());
double yd = based * std::abs(internal::random<double>());
VectorXf vf = VectorXf::Ones(s) * yf;
VectorXd vd = VectorXd::Ones(s) * yd;
std::cout << "reference\t" << std::sqrt(double(s))*yf << "\t" << std::sqrt(double(s))*yd << "\n";
std::cout << "sqsumNorm\t" << sqsumNorm(vf) << "\t" << sqsumNorm(vd) << "\n";
std::cout << "hypotNorm\t" << hypotNorm(vf) << "\t" << hypotNorm(vd) << "\n";
std::cout << "blueNorm\t" << blueNorm(vf) << "\t" << blueNorm(vd) << "\n";
std::cout << "pblueNorm\t" << pblueNorm(vf) << "\t" << pblueNorm(vd) << "\n";
std::cout << "lapackNorm\t" << lapackNorm(vf) << "\t" << lapackNorm(vd) << "\n";
std::cout << "twopassNorm\t" << twopassNorm(vf) << "\t" << twopassNorm(vd) << "\n";
std::cout << "bl2passNorm\t" << bl2passNorm(vf) << "\t" << bl2passNorm(vd) << "\n";
}
void check_accuracy_var(int ef0, int ef1, int ed0, int ed1, int s)
{
VectorXf vf(s);
VectorXd vd(s);
for (int i=0; i<s; ++i)
{
vf[i] = std::abs(internal::random<double>()) * std::pow(double(10), internal::random<int>(ef0,ef1));
vd[i] = std::abs(internal::random<double>()) * std::pow(double(10), internal::random<int>(ed0,ed1));
}
//std::cout << "reference\t" << internal::sqrt(double(s))*yf << "\t" << internal::sqrt(double(s))*yd << "\n";
std::cout << "sqsumNorm\t" << sqsumNorm(vf) << "\t" << sqsumNorm(vd) << "\t" << sqsumNorm(vf.cast<long double>()) << "\t" << sqsumNorm(vd.cast<long double>()) << "\n";
std::cout << "hypotNorm\t" << hypotNorm(vf) << "\t" << hypotNorm(vd) << "\t" << hypotNorm(vf.cast<long double>()) << "\t" << hypotNorm(vd.cast<long double>()) << "\n";
std::cout << "blueNorm\t" << blueNorm(vf) << "\t" << blueNorm(vd) << "\t" << blueNorm(vf.cast<long double>()) << "\t" << blueNorm(vd.cast<long double>()) << "\n";
std::cout << "pblueNorm\t" << pblueNorm(vf) << "\t" << pblueNorm(vd) << "\t" << blueNorm(vf.cast<long double>()) << "\t" << blueNorm(vd.cast<long double>()) << "\n";
std::cout << "lapackNorm\t" << lapackNorm(vf) << "\t" << lapackNorm(vd) << "\t" << lapackNorm(vf.cast<long double>()) << "\t" << lapackNorm(vd.cast<long double>()) << "\n";
std::cout << "twopassNorm\t" << twopassNorm(vf) << "\t" << twopassNorm(vd) << "\t" << twopassNorm(vf.cast<long double>()) << "\t" << twopassNorm(vd.cast<long double>()) << "\n";
// std::cout << "bl2passNorm\t" << bl2passNorm(vf) << "\t" << bl2passNorm(vd) << "\t" << bl2passNorm(vf.cast<long double>()) << "\t" << bl2passNorm(vd.cast<long double>()) << "\n";
}
int main(int argc, char** argv)
{
int tries = 10;
int iters = 100000;
double y = 1.1345743233455785456788e12 * internal::random<double>();
VectorXf v = VectorXf::Ones(1024) * y;
// return 0;
int s = 10000;
double basef_ok = 1.1345743233455785456788e15;
double based_ok = 1.1345743233455785456788e95;
double basef_under = 1.1345743233455785456788e-27;
double based_under = 1.1345743233455785456788e-303;
double basef_over = 1.1345743233455785456788e+27;
double based_over = 1.1345743233455785456788e+302;
std::cout.precision(20);
std::cerr << "\nNo under/overflow:\n";
check_accuracy(basef_ok, based_ok, s);
std::cerr << "\nUnderflow:\n";
check_accuracy(basef_under, based_under, s);
std::cerr << "\nOverflow:\n";
check_accuracy(basef_over, based_over, s);
std::cerr << "\nVarying (over):\n";
for (int k=0; k<1; ++k)
{
check_accuracy_var(20,27,190,302,s);
std::cout << "\n";
}
std::cerr << "\nVarying (under):\n";
for (int k=0; k<1; ++k)
{
check_accuracy_var(-27,20,-302,-190,s);
std::cout << "\n";
}
y = 1;
std::cout.precision(4);
int s1 = 1024*1024*32;
std::cerr << "Performance (out of cache, " << s1 << "):\n";
{
int iters = 1;
VectorXf vf = VectorXf::Random(s1) * y;
VectorXd vd = VectorXd::Random(s1) * y;
VectorXcf vcf = VectorXcf::Random(s1) * y;
BENCH_PERF(sqsumNorm);
BENCH_PERF(stableNorm);
BENCH_PERF(blueNorm);
BENCH_PERF(pblueNorm);
BENCH_PERF(lapackNorm);
BENCH_PERF(hypotNorm);
BENCH_PERF(twopassNorm);
BENCH_PERF(bl2passNorm);
}
std::cerr << "\nPerformance (in cache, " << 512 << "):\n";
{
int iters = 100000;
VectorXf vf = VectorXf::Random(512) * y;
VectorXd vd = VectorXd::Random(512) * y;
VectorXcf vcf = VectorXcf::Random(512) * y;
BENCH_PERF(sqsumNorm);
BENCH_PERF(stableNorm);
BENCH_PERF(blueNorm);
BENCH_PERF(pblueNorm);
BENCH_PERF(lapackNorm);
BENCH_PERF(hypotNorm);
BENCH_PERF(twopassNorm);
BENCH_PERF(bl2passNorm);
}
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/benchmark.cpp | .cpp | 790 | 40 | // g++ -O3 -DNDEBUG -DMATSIZE=<x> benchmark.cpp -o benchmark && time ./benchmark
#include <iostream>
#include <Eigen/Core>
#ifndef MATSIZE
#define MATSIZE 3
#endif
using namespace std;
using namespace Eigen;
#ifndef REPEAT
#define REPEAT 40000000
#endif
#ifndef SCALAR
#define SCALAR double
#endif
int main(int argc, char *argv[])
{
Matrix<SCALAR,MATSIZE,MATSIZE> I = Matrix<SCALAR,MATSIZE,MATSIZE>::Ones();
Matrix<SCALAR,MATSIZE,MATSIZE> m;
for(int i = 0; i < MATSIZE; i++)
for(int j = 0; j < MATSIZE; j++)
{
m(i,j) = (i+MATSIZE*j);
}
asm("#begin");
for(int a = 0; a < REPEAT; a++)
{
m = Matrix<SCALAR,MATSIZE,MATSIZE>::Ones() + 0.00005 * (m + (m*m));
}
asm("#end");
cout << m << endl;
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/generic_bench/btl.hh | .hh | 6,748 | 243 | //=====================================================
// File : btl.hh
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#ifndef BTL_HH
#define BTL_HH
#include "bench_parameter.hh"
#include <iostream>
#include <algorithm>
#include <vector>
#include <string>
#include "utilities.h"
#if (defined __GNUC__)
#define BTL_ALWAYS_INLINE __attribute__((always_inline)) inline
#else
#define BTL_ALWAYS_INLINE inline
#endif
#if (defined __GNUC__)
#define BTL_DONT_INLINE __attribute__((noinline))
#else
#define BTL_DONT_INLINE
#endif
#if (defined __GNUC__)
#define BTL_ASM_COMMENT(X) asm("#" X)
#else
#define BTL_ASM_COMMENT(X)
#endif
#ifdef __SSE__
#include "xmmintrin.h"
// This enables flush to zero (FTZ) and denormals are zero (DAZ) modes:
#define BTL_DISABLE_SSE_EXCEPTIONS() { _mm_setcsr(_mm_getcsr() | 0x8040); }
#else
#define BTL_DISABLE_SSE_EXCEPTIONS()
#endif
/** Enhanced std::string
*/
class BtlString : public std::string
{
public:
BtlString() : std::string() {}
BtlString(const BtlString& str) : std::string(static_cast<const std::string&>(str)) {}
BtlString(const std::string& str) : std::string(str) {}
BtlString(const char* str) : std::string(str) {}
operator const char* () const { return c_str(); }
void trim( bool left = true, bool right = true )
{
int lspaces, rspaces, len = length(), i;
lspaces = rspaces = 0;
if ( left )
for (i=0; i<len && (at(i)==' '||at(i)=='\t'||at(i)=='\r'||at(i)=='\n'); ++lspaces,++i);
if ( right && lspaces < len )
for(i=len-1; i>=0 && (at(i)==' '||at(i)=='\t'||at(i)=='\r'||at(i)=='\n'); rspaces++,i--);
*this = substr(lspaces, len-lspaces-rspaces);
}
std::vector<BtlString> split( const BtlString& delims = "\t\n ") const
{
std::vector<BtlString> ret;
unsigned int numSplits = 0;
size_t start, pos;
start = 0;
do
{
pos = find_first_of(delims, start);
if (pos == start)
{
ret.push_back("");
start = pos + 1;
}
else if (pos == npos)
ret.push_back( substr(start) );
else
{
ret.push_back( substr(start, pos - start) );
start = pos + 1;
}
//start = find_first_not_of(delims, start);
++numSplits;
} while (pos != npos);
return ret;
}
bool endsWith(const BtlString& str) const
{
if(str.size()>this->size())
return false;
return this->substr(this->size()-str.size(),str.size()) == str;
}
bool contains(const BtlString& str) const
{
return this->find(str)<this->size();
}
bool beginsWith(const BtlString& str) const
{
if(str.size()>this->size())
return false;
return this->substr(0,str.size()) == str;
}
BtlString toLowerCase( void )
{
std::transform(begin(), end(), begin(), static_cast<int(*)(int)>(::tolower) );
return *this;
}
BtlString toUpperCase( void )
{
std::transform(begin(), end(), begin(), static_cast<int(*)(int)>(::toupper) );
return *this;
}
/** Case insensitive comparison.
*/
bool isEquiv(const BtlString& str) const
{
BtlString str0 = *this;
str0.toLowerCase();
BtlString str1 = str;
str1.toLowerCase();
return str0 == str1;
}
/** Decompose the current string as a path and a file.
For instance: "dir1/dir2/file.ext" leads to path="dir1/dir2/" and filename="file.ext"
*/
void decomposePathAndFile(BtlString& path, BtlString& filename) const
{
std::vector<BtlString> elements = this->split("/\\");
path = "";
filename = elements.back();
elements.pop_back();
if (this->at(0)=='/')
path = "/";
for (unsigned int i=0 ; i<elements.size() ; ++i)
path += elements[i] + "/";
}
};
class BtlConfig
{
public:
BtlConfig()
: overwriteResults(false), checkResults(true), realclock(false), tries(DEFAULT_NB_TRIES)
{
char * _config;
_config = getenv ("BTL_CONFIG");
if (_config!=NULL)
{
std::vector<BtlString> config = BtlString(_config).split(" \t\n");
for (unsigned int i = 0; i<config.size(); i++)
{
if (config[i].beginsWith("-a"))
{
if (i+1==config.size())
{
std::cerr << "error processing option: " << config[i] << "\n";
exit(2);
}
Instance.m_selectedActionNames = config[i+1].split(":");
i += 1;
}
else if (config[i].beginsWith("-t"))
{
if (i+1==config.size())
{
std::cerr << "error processing option: " << config[i] << "\n";
exit(2);
}
Instance.tries = atoi(config[i+1].c_str());
i += 1;
}
else if (config[i].beginsWith("--overwrite"))
{
Instance.overwriteResults = true;
}
else if (config[i].beginsWith("--nocheck"))
{
Instance.checkResults = false;
}
else if (config[i].beginsWith("--real"))
{
Instance.realclock = true;
}
}
}
BTL_DISABLE_SSE_EXCEPTIONS();
}
BTL_DONT_INLINE static bool skipAction(const std::string& _name)
{
if (Instance.m_selectedActionNames.empty())
return false;
BtlString name(_name);
for (unsigned int i=0; i<Instance.m_selectedActionNames.size(); ++i)
if (name.contains(Instance.m_selectedActionNames[i]))
return false;
return true;
}
static BtlConfig Instance;
bool overwriteResults;
bool checkResults;
bool realclock;
int tries;
protected:
std::vector<BtlString> m_selectedActionNames;
};
#define BTL_MAIN \
BtlConfig BtlConfig::Instance
#endif // BTL_HH
| Unknown |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/generic_bench/bench.hh | .hh | 4,827 | 169 | //=====================================================
// File : bench.hh
// Author : L. Plagne <laurent.plagne@edf.fr)>
// Copyright (C) EDF R&D, lun sep 30 14:23:16 CEST 2002
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#ifndef BENCH_HH
#define BENCH_HH
#include "btl.hh"
#include "bench_parameter.hh"
#include <iostream>
#include "utilities.h"
#include "size_lin_log.hh"
#include "xy_file.hh"
#include <vector>
#include <string>
#include "timers/portable_perf_analyzer.hh"
// #include "timers/mixed_perf_analyzer.hh"
// #include "timers/x86_perf_analyzer.hh"
// #include "timers/STL_perf_analyzer.hh"
#ifdef HAVE_MKL
extern "C" void cblas_saxpy(const int, const float, const float*, const int, float *, const int);
#endif
using namespace std;
template <template<class> class Perf_Analyzer, class Action>
BTL_DONT_INLINE void bench( int size_min, int size_max, int nb_point )
{
if (BtlConfig::skipAction(Action::name()))
return;
string filename="bench_"+Action::name()+".dat";
INFOS("starting " <<filename);
// utilities
std::vector<double> tab_mflops(nb_point);
std::vector<int> tab_sizes(nb_point);
// matrices and vector size calculations
size_lin_log(nb_point,size_min,size_max,tab_sizes);
std::vector<int> oldSizes;
std::vector<double> oldFlops;
bool hasOldResults = read_xy_file(filename, oldSizes, oldFlops, true);
int oldi = oldSizes.size() - 1;
// loop on matrix size
Perf_Analyzer<Action> perf_action;
for (int i=nb_point-1;i>=0;i--)
{
//INFOS("size=" <<tab_sizes[i]<<" ("<<nb_point-i<<"/"<<nb_point<<")");
std::cout << " " << "size = " << tab_sizes[i] << " " << std::flush;
BTL_DISABLE_SSE_EXCEPTIONS();
#ifdef HAVE_MKL
{
float dummy;
cblas_saxpy(1,0,&dummy,1,&dummy,1);
}
#endif
tab_mflops[i] = perf_action.eval_mflops(tab_sizes[i]);
std::cout << tab_mflops[i];
if (hasOldResults)
{
while (oldi>=0 && oldSizes[oldi]>tab_sizes[i])
--oldi;
if (oldi>=0 && oldSizes[oldi]==tab_sizes[i])
{
if (oldFlops[oldi]<tab_mflops[i])
std::cout << "\t > ";
else
std::cout << "\t < ";
std::cout << oldFlops[oldi];
}
--oldi;
}
std::cout << " MFlops (" << nb_point-i << "/" << nb_point << ")" << std::endl;
}
if (!BtlConfig::Instance.overwriteResults)
{
if (hasOldResults)
{
// merge the two data
std::vector<int> newSizes;
std::vector<double> newFlops;
unsigned int i=0;
unsigned int j=0;
while (i<tab_sizes.size() && j<oldSizes.size())
{
if (tab_sizes[i] == oldSizes[j])
{
newSizes.push_back(tab_sizes[i]);
newFlops.push_back(std::max(tab_mflops[i], oldFlops[j]));
++i;
++j;
}
else if (tab_sizes[i] < oldSizes[j])
{
newSizes.push_back(tab_sizes[i]);
newFlops.push_back(tab_mflops[i]);
++i;
}
else
{
newSizes.push_back(oldSizes[j]);
newFlops.push_back(oldFlops[j]);
++j;
}
}
while (i<tab_sizes.size())
{
newSizes.push_back(tab_sizes[i]);
newFlops.push_back(tab_mflops[i]);
++i;
}
while (j<oldSizes.size())
{
newSizes.push_back(oldSizes[j]);
newFlops.push_back(oldFlops[j]);
++j;
}
tab_mflops = newFlops;
tab_sizes = newSizes;
}
}
// dump the result in a file :
dump_xy_file(tab_sizes,tab_mflops,filename);
}
// default Perf Analyzer
template <class Action>
BTL_DONT_INLINE void bench( int size_min, int size_max, int nb_point ){
// if the rdtsc is not available :
bench<Portable_Perf_Analyzer,Action>(size_min,size_max,nb_point);
// if the rdtsc is available :
// bench<Mixed_Perf_Analyzer,Action>(size_min,size_max,nb_point);
// Only for small problem size. Otherwize it will be too long
// bench<X86_Perf_Analyzer,Action>(size_min,size_max,nb_point);
// bench<STL_Perf_Analyzer,Action>(size_min,size_max,nb_point);
}
#endif
| Unknown |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/generic_bench/bench_parameter.hh | .hh | 1,916 | 54 | //=====================================================
// File : bench_parameter.hh
// Author : L. Plagne <laurent.plagne@edf.fr)>
// Copyright (C) EDF R&D, lun sep 30 14:23:16 CEST 2002
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#ifndef BENCH_PARAMETER_HH
#define BENCH_PARAMETER_HH
// minimal time for each measurement
#define REAL_TYPE float
// minimal time for each measurement
#define MIN_TIME 0.2
// nb of point on bench curves
#define NB_POINT 100
// min vector size for axpy bench
#define MIN_AXPY 5
// max vector size for axpy bench
#define MAX_AXPY 3000000
// min matrix size for matrix vector product bench
#define MIN_MV 5
// max matrix size for matrix vector product bench
#define MAX_MV 5000
// min matrix size for matrix matrix product bench
#define MIN_MM 5
// max matrix size for matrix matrix product bench
#define MAX_MM MAX_MV
// min matrix size for LU bench
#define MIN_LU 5
// max matrix size for LU bench
#define MAX_LU 3000
// max size for tiny vector and matrix
#define TINY_MV_MAX_SIZE 16
// default nb_sample for x86 timer
#define DEFAULT_NB_SAMPLE 1000
// how many times we run a single bench (keep the best perf)
#define DEFAULT_NB_TRIES 3
#endif
| Unknown |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/generic_bench/utils/utilities.h | .h | 2,745 | 91 | //=============================================================================
// File : utilities.h
// Created : mar jun 19 13:18:14 CEST 2001
// Author : Antoine YESSAYAN, Paul RASCLE, EDF
// Project : SALOME
// Copyright : EDF 2001
// $Header$
//=============================================================================
/* --- Definition macros file to print information if _DEBUG_ is defined --- */
# ifndef UTILITIES_H
# define UTILITIES_H
# include <stdlib.h>
//# include <iostream> ok for gcc3.01
# include <iostream>
/* --- INFOS is always defined (without _DEBUG_): to be used for warnings, with release version --- */
# define HEREWEARE cout<<flush ; cerr << __FILE__ << " [" << __LINE__ << "] : " << flush ;
# define INFOS(chain) {HEREWEARE ; cerr << chain << endl ;}
# define PYSCRIPT(chain) {cout<<flush ; cerr << "---PYSCRIPT--- " << chain << endl ;}
/* --- To print date and time of compilation of current source on stdout --- */
# if defined ( __GNUC__ )
# define COMPILER "g++" ;
# elif defined ( __sun )
# define COMPILER "CC" ;
# elif defined ( __KCC )
# define COMPILER "KCC" ;
# elif defined ( __PGI )
# define COMPILER "pgCC" ;
# else
# define COMPILER "undefined" ;
# endif
# ifdef INFOS_COMPILATION
# error INFOS_COMPILATION already defined
# endif
# define INFOS_COMPILATION {\
cerr << flush;\
cout << __FILE__ ;\
cout << " [" << __LINE__ << "] : " ;\
cout << "COMPILED with " << COMPILER ;\
cout << ", " << __DATE__ ; \
cout << " at " << __TIME__ << endl ;\
cout << "\n\n" ;\
cout << flush ;\
}
# ifdef _DEBUG_
/* --- the following MACROS are useful at debug time --- */
# define HERE cout<<flush ; cerr << "- Trace " << __FILE__ << " [" << __LINE__ << "] : " << flush ;
# define SCRUTE(var) HERE ; cerr << #var << "=" << var << endl ;
# define MESSAGE(chain) {HERE ; cerr << chain << endl ;}
# define INTERRUPTION(code) HERE ; cerr << "INTERRUPTION return code= " << code << endl ; exit(code) ;
# ifndef ASSERT
# define ASSERT(condition) if (!(condition)){ HERE ; cerr << "CONDITION " << #condition << " NOT VERIFIED"<< endl ; INTERRUPTION(1) ;}
# endif /* ASSERT */
#define REPERE cout<<flush ; cerr << " --------------" << endl << flush ;
#define BEGIN_OF(chain) {REPERE ; HERE ; cerr << "Begin of: " << chain << endl ; REPERE ; }
#define END_OF(chain) {REPERE ; HERE ; cerr << "Normal end of: " << chain << endl ; REPERE ; }
# else /* ifdef _DEBUG_*/
# define HERE
# define SCRUTE(var)
# define MESSAGE(chain)
# define INTERRUPTION(code)
# ifndef ASSERT
# define ASSERT(condition)
# endif /* ASSERT */
#define REPERE
#define BEGIN_OF(chain)
#define END_OF(chain)
# endif /* ifdef _DEBUG_*/
# endif /* ifndef UTILITIES_H */
| Unknown |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/generic_bench/utils/size_log.hh | .hh | 1,645 | 55 | //=====================================================
// File : size_log.hh
// Author : L. Plagne <laurent.plagne@edf.fr)>
// Copyright (C) EDF R&D, lun sep 30 14:23:17 CEST 2002
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#ifndef SIZE_LOG
#define SIZE_LOG
#include "math.h"
// The Vector class must satisfy the following part of STL vector concept :
// resize() method
// [] operator for seting element
// the vector element are int compatible.
template<class Vector>
void size_log(const int nb_point, const int size_min, const int size_max, Vector & X)
{
X.resize(nb_point);
float ls_min=log(float(size_min));
float ls_max=log(float(size_max));
float ls=0.0;
float delta_ls=(ls_max-ls_min)/(float(nb_point-1));
int size=0;
for (int i=0;i<nb_point;i++){
ls = ls_min + float(i)*delta_ls ;
size=int(exp(ls));
X[i]=size;
}
}
#endif
| Unknown |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/generic_bench/utils/xy_file.hh | .hh | 2,213 | 76 | //=====================================================
// File : dump_file_x_y.hh
// Author : L. Plagne <laurent.plagne@edf.fr)>
// Copyright (C) EDF R&D, lun sep 30 14:23:20 CEST 2002
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#ifndef XY_FILE_HH
#define XY_FILE_HH
#include <fstream>
#include <iostream>
#include <string>
#include <vector>
using namespace std;
bool read_xy_file(const std::string & filename, std::vector<int> & tab_sizes,
std::vector<double> & tab_mflops, bool quiet = false)
{
std::ifstream input_file (filename.c_str(),std::ios::in);
if (!input_file){
if (!quiet) {
INFOS("!!! Error opening "<<filename);
}
return false;
}
int nb_point=0;
int size=0;
double mflops=0;
while (input_file >> size >> mflops ){
nb_point++;
tab_sizes.push_back(size);
tab_mflops.push_back(mflops);
}
SCRUTE(nb_point);
input_file.close();
return true;
}
// The Vector class must satisfy the following part of STL vector concept :
// resize() method
// [] operator for seting element
// the vector element must have the << operator define
using namespace std;
template<class Vector_A, class Vector_B>
void dump_xy_file(const Vector_A & X, const Vector_B & Y, const std::string & filename){
ofstream outfile (filename.c_str(),ios::out) ;
int size=X.size();
for (int i=0;i<size;i++)
outfile << X[i] << " " << Y[i] << endl;
outfile.close();
}
#endif
| Unknown |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/generic_bench/init/init_function.hh | .hh | 1,478 | 55 | //=====================================================
// File : init_function.hh
// Author : L. Plagne <laurent.plagne@edf.fr)>
// Copyright (C) EDF R&D, lun sep 30 14:23:18 CEST 2002
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#ifndef INIT_FUNCTION_HH
#define INIT_FUNCTION_HH
double simple_function(int index)
{
return index;
}
double simple_function(int index_i, int index_j)
{
return index_i+index_j;
}
double pseudo_random(int /*index*/)
{
return std::rand()/double(RAND_MAX);
}
double pseudo_random(int /*index_i*/, int /*index_j*/)
{
return std::rand()/double(RAND_MAX);
}
double null_function(int /*index*/)
{
return 0.0;
}
double null_function(int /*index_i*/, int /*index_j*/)
{
return 0.0;
}
#endif
| Unknown |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/generic_bench/init/init_vector.hh | .hh | 1,416 | 38 | //=====================================================
// File : init_vector.hh
// Author : L. Plagne <laurent.plagne@edf.fr)>
// Copyright (C) EDF R&D, lun sep 30 14:23:18 CEST 2002
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#ifndef INIT_VECTOR_HH
#define INIT_VECTOR_HH
// The Vector class must satisfy the following part of STL vector concept :
// resize() method
// [] operator for setting element
// value_type defined
template<double init_function(int), class Vector>
void init_vector(Vector & X, int size){
X.resize(size);
for (unsigned int i=0;i<X.size();i++){
X[i]=typename Vector::value_type(init_function(i));
}
}
#endif
| Unknown |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/generic_bench/init/init_matrix.hh | .hh | 2,295 | 65 | //=====================================================
// File : init_matrix.hh
// Author : L. Plagne <laurent.plagne@edf.fr)>
// Copyright (C) EDF R&D, lun sep 30 14:23:19 CEST 2002
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#ifndef INIT_MATRIX_HH
#define INIT_MATRIX_HH
// The Vector class must satisfy the following part of STL vector concept :
// resize() method
// [] operator for setting element
// value_type defined
template<double init_function(int,int), class Vector>
BTL_DONT_INLINE void init_row(Vector & X, int size, int row){
X.resize(size);
for (unsigned int j=0;j<X.size();j++){
X[j]=typename Vector::value_type(init_function(row,j));
}
}
// Matrix is a Vector of Vector
// The Matrix class must satisfy the following part of STL vector concept :
// resize() method
// [] operator for setting rows
template<double init_function(int,int),class Vector>
BTL_DONT_INLINE void init_matrix(Vector & A, int size){
A.resize(size);
for (unsigned int row=0; row<A.size() ; row++){
init_row<init_function>(A[row],size,row);
}
}
template<double init_function(int,int),class Matrix>
BTL_DONT_INLINE void init_matrix_symm(Matrix& A, int size){
A.resize(size);
for (unsigned int row=0; row<A.size() ; row++)
A[row].resize(size);
for (unsigned int row=0; row<A.size() ; row++){
A[row][row] = init_function(row,row);
for (unsigned int col=0; col<row ; col++){
double x = init_function(row,col);
A[row][col] = A[col][row] = x;
}
}
}
#endif
| Unknown |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/generic_bench/timers/portable_perf_analyzer.hh | .hh | 2,938 | 104 | //=====================================================
// File : portable_perf_analyzer.hh
// Author : L. Plagne <laurent.plagne@edf.fr)>
// Copyright (C) EDF R&D, mar d�c 3 18:59:35 CET 2002
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#ifndef _PORTABLE_PERF_ANALYZER_HH
#define _PORTABLE_PERF_ANALYZER_HH
#include "utilities.h"
#include "timers/portable_timer.hh"
template <class Action>
class Portable_Perf_Analyzer{
public:
Portable_Perf_Analyzer( ):_nb_calc(0), m_time_action(0), _chronos(){
MESSAGE("Portable_Perf_Analyzer Ctor");
};
Portable_Perf_Analyzer( const Portable_Perf_Analyzer & ){
INFOS("Copy Ctor not implemented");
exit(0);
};
~Portable_Perf_Analyzer(){
MESSAGE("Portable_Perf_Analyzer Dtor");
};
BTL_DONT_INLINE double eval_mflops(int size)
{
Action action(size);
// action.initialize();
// time_action = time_calculate(action);
while (m_time_action < MIN_TIME)
{
if(_nb_calc==0) _nb_calc = 1;
else _nb_calc *= 2;
action.initialize();
m_time_action = time_calculate(action);
}
// optimize
for (int i=1; i<BtlConfig::Instance.tries; ++i)
{
Action _action(size);
std::cout << " " << _action.nb_op_base()*_nb_calc/(m_time_action*1e6) << " ";
_action.initialize();
m_time_action = std::min(m_time_action, time_calculate(_action));
}
double time_action = m_time_action / (double(_nb_calc));
// check
if (BtlConfig::Instance.checkResults && size<128)
{
action.initialize();
action.calculate();
action.check_result();
}
return action.nb_op_base()/(time_action*1e6);
}
BTL_DONT_INLINE double time_calculate(Action & action)
{
// time measurement
action.calculate();
_chronos.start();
for (unsigned int ii=0;ii<_nb_calc;ii++)
{
action.calculate();
}
_chronos.stop();
return _chronos.user_time();
}
unsigned long long get_nb_calc()
{
return _nb_calc;
}
private:
unsigned long long _nb_calc;
double m_time_action;
Portable_Timer _chronos;
};
#endif //_PORTABLE_PERF_ANALYZER_HH
| Unknown |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/generic_bench/timers/portable_perf_analyzer_old.hh | .hh | 3,534 | 135 | //=====================================================
// File : portable_perf_analyzer.hh
// Author : L. Plagne <laurent.plagne@edf.fr)>
// Copyright (C) EDF R&D, mar d�c 3 18:59:35 CET 2002
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#ifndef _PORTABLE_PERF_ANALYZER_HH
#define _PORTABLE_PERF_ANALYZER_HH
#include "utilities.h"
#include "timers/portable_timer.hh"
template <class Action>
class Portable_Perf_Analyzer{
public:
Portable_Perf_Analyzer( void ):_nb_calc(1),_nb_init(1),_chronos(){
MESSAGE("Portable_Perf_Analyzer Ctor");
};
Portable_Perf_Analyzer( const Portable_Perf_Analyzer & ){
INFOS("Copy Ctor not implemented");
exit(0);
};
~Portable_Perf_Analyzer( void ){
MESSAGE("Portable_Perf_Analyzer Dtor");
};
inline double eval_mflops(int size)
{
Action action(size);
// double time_baseline = time_init(action);
// while (time_baseline < MIN_TIME_INIT)
// {
// _nb_init *= 2;
// time_baseline = time_init(action);
// }
//
// // optimize
// for (int i=1; i<NB_TRIES; ++i)
// time_baseline = std::min(time_baseline, time_init(action));
//
// time_baseline = time_baseline/(double(_nb_init));
double time_action = time_calculate(action);
while (time_action < MIN_TIME)
{
_nb_calc *= 2;
time_action = time_calculate(action);
}
// optimize
for (int i=1; i<NB_TRIES; ++i)
time_action = std::min(time_action, time_calculate(action));
// INFOS("size="<<size);
// INFOS("_nb_init="<<_nb_init);
// INFOS("_nb_calc="<<_nb_calc);
time_action = time_action / (double(_nb_calc));
action.check_result();
double time_baseline = time_init(action);
for (int i=1; i<NB_TRIES; ++i)
time_baseline = std::min(time_baseline, time_init(action));
time_baseline = time_baseline/(double(_nb_init));
// INFOS("time_baseline="<<time_baseline);
// INFOS("time_action="<<time_action);
time_action = time_action - time_baseline;
// INFOS("time_corrected="<<time_action);
return action.nb_op_base()/(time_action*1000000.0);
}
inline double time_init(Action & action)
{
// time measurement
_chronos.start();
for (int ii=0; ii<_nb_init; ii++)
action.initialize();
_chronos.stop();
return _chronos.user_time();
}
inline double time_calculate(Action & action)
{
// time measurement
_chronos.start();
for (int ii=0;ii<_nb_calc;ii++)
{
action.initialize();
action.calculate();
}
_chronos.stop();
return _chronos.user_time();
}
unsigned long long get_nb_calc( void )
{
return _nb_calc;
}
private:
unsigned long long _nb_calc;
unsigned long long _nb_init;
Portable_Timer _chronos;
};
#endif //_PORTABLE_PERF_ANALYZER_HH
| Unknown |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/generic_bench/timers/portable_timer.hh | .hh | 3,534 | 188 | //=====================================================
// File : portable_timer.hh
// Author : L. Plagne <laurent.plagne@edf.fr)> from boost lib
// Copyright (C) EDF R&D, lun sep 30 14:23:17 CEST 2002
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
// simple_time extracted from the boost library
//
#ifndef _PORTABLE_TIMER_HH
#define _PORTABLE_TIMER_HH
#include <ctime>
#include <cstdlib>
#include <time.h>
#define USEC_IN_SEC 1000000
// timer -------------------------------------------------------------------//
// A timer object measures CPU time.
#if defined(_MSC_VER)
#define NOMINMAX
#include <windows.h>
/*#ifndef hr_timer
#include "hr_time.h"
#define hr_timer
#endif*/
class Portable_Timer
{
public:
typedef struct {
LARGE_INTEGER start;
LARGE_INTEGER stop;
} stopWatch;
Portable_Timer()
{
startVal.QuadPart = 0;
stopVal.QuadPart = 0;
QueryPerformanceFrequency(&frequency);
}
void start() { QueryPerformanceCounter(&startVal); }
void stop() { QueryPerformanceCounter(&stopVal); }
double elapsed() {
LARGE_INTEGER time;
time.QuadPart = stopVal.QuadPart - startVal.QuadPart;
return LIToSecs(time);
}
double user_time() { return elapsed(); }
private:
double LIToSecs(LARGE_INTEGER& L) {
return ((double)L.QuadPart /(double)frequency.QuadPart) ;
}
LARGE_INTEGER startVal;
LARGE_INTEGER stopVal;
LARGE_INTEGER frequency;
}; // Portable_Timer
#elif defined(__APPLE__)
#include <CoreServices/CoreServices.h>
#include <mach/mach_time.h>
class Portable_Timer
{
public:
Portable_Timer()
{
}
void start()
{
m_start_time = double(mach_absolute_time())*1e-9;;
}
void stop()
{
m_stop_time = double(mach_absolute_time())*1e-9;;
}
double elapsed()
{
return user_time();
}
double user_time()
{
return m_stop_time - m_start_time;
}
private:
double m_stop_time, m_start_time;
}; // Portable_Timer (Apple)
#else
#include <sys/time.h>
#include <sys/resource.h>
#include <unistd.h>
#include <sys/times.h>
class Portable_Timer
{
public:
Portable_Timer()
{
m_clkid = BtlConfig::Instance.realclock ? CLOCK_REALTIME : CLOCK_PROCESS_CPUTIME_ID;
}
Portable_Timer(int clkid) : m_clkid(clkid)
{}
void start()
{
timespec ts;
clock_gettime(m_clkid, &ts);
m_start_time = double(ts.tv_sec) + 1e-9 * double(ts.tv_nsec);
}
void stop()
{
timespec ts;
clock_gettime(m_clkid, &ts);
m_stop_time = double(ts.tv_sec) + 1e-9 * double(ts.tv_nsec);
}
double elapsed()
{
return user_time();
}
double user_time()
{
return m_stop_time - m_start_time;
}
private:
int m_clkid;
double m_stop_time, m_start_time;
}; // Portable_Timer (Linux)
#endif
#endif // PORTABLE_TIMER_HPP
| Unknown |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/generic_bench/timers/x86_perf_analyzer.hh | .hh | 2,927 | 109 | //=====================================================
// File : x86_perf_analyzer.hh
// Author : L. Plagne <laurent.plagne@edf.fr)>
// Copyright (C) EDF R&D, mar d�c 3 18:59:35 CET 2002
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#ifndef _X86_PERF_ANALYSER_HH
#define _X86_PERF_ANALYSER_HH
#include "x86_timer.hh"
#include "bench_parameter.hh"
template<class ACTION>
class X86_Perf_Analyzer{
public:
X86_Perf_Analyzer( unsigned long long nb_sample=DEFAULT_NB_SAMPLE):_nb_sample(nb_sample),_chronos()
{
MESSAGE("X86_Perf_Analyzer Ctor");
_chronos.find_frequency();
};
X86_Perf_Analyzer( const X86_Perf_Analyzer & ){
INFOS("Copy Ctor not implemented");
exit(0);
};
~X86_Perf_Analyzer( void ){
MESSAGE("X86_Perf_Analyzer Dtor");
};
inline double eval_mflops(int size)
{
ACTION action(size);
int nb_loop=5;
double calculate_time=0.0;
double baseline_time=0.0;
for (int j=0 ; j < nb_loop ; j++){
_chronos.clear();
for(int i=0 ; i < _nb_sample ; i++)
{
_chronos.start();
action.initialize();
action.calculate();
_chronos.stop();
_chronos.add_get_click();
}
calculate_time += double(_chronos.get_shortest_clicks())/_chronos.frequency();
if (j==0) action.check_result();
_chronos.clear();
for(int i=0 ; i < _nb_sample ; i++)
{
_chronos.start();
action.initialize();
_chronos.stop();
_chronos.add_get_click();
}
baseline_time+=double(_chronos.get_shortest_clicks())/_chronos.frequency();
}
double corrected_time = (calculate_time-baseline_time)/double(nb_loop);
// INFOS("_nb_sample="<<_nb_sample);
// INFOS("baseline_time="<<baseline_time);
// INFOS("calculate_time="<<calculate_time);
// INFOS("corrected_time="<<corrected_time);
// cout << size <<" "<<baseline_time<<" "<<calculate_time<<" "<<corrected_time<<" "<<action.nb_op_base() << endl;
return action.nb_op_base()/(corrected_time*1000000.0);
//return action.nb_op_base()/(calculate_time*1000000.0);
}
private:
X86_Timer _chronos;
unsigned long long _nb_sample;
};
#endif
| Unknown |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/generic_bench/timers/x86_timer.hh | .hh | 5,294 | 247 | //=====================================================
// File : x86_timer.hh
// Author : L. Plagne <laurent.plagne@edf.fr)>
// Copyright (C) EDF R&D, mar d�c 3 18:59:35 CET 2002
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#ifndef _X86_TIMER_HH
#define _X86_TIMER_HH
#include <sys/time.h>
#include <sys/resource.h>
#include <unistd.h>
#include <sys/times.h>
//#include "system_time.h"
#define u32 unsigned int
#include <asm/msr.h>
#include "utilities.h"
#include <map>
#include <fstream>
#include <string>
#include <iostream>
// frequence de la becanne en Hz
//#define FREQUENCY 648000000
//#define FREQUENCY 1400000000
#define FREQUENCY 1695000000
using namespace std;
class X86_Timer {
public :
X86_Timer( void ):_frequency(FREQUENCY),_nb_sample(0)
{
MESSAGE("X86_Timer Default Ctor");
}
inline void start( void ){
rdtsc(_click_start.n32[0],_click_start.n32[1]);
}
inline void stop( void ){
rdtsc(_click_stop.n32[0],_click_stop.n32[1]);
}
inline double frequency( void ){
return _frequency;
}
double get_elapsed_time_in_second( void ){
return (_click_stop.n64-_click_start.n64)/double(FREQUENCY);
}
unsigned long long get_click( void ){
return (_click_stop.n64-_click_start.n64);
}
inline void find_frequency( void ){
time_t initial, final;
int dummy=2;
initial = time(0);
start();
do {
dummy+=2;
}
while(time(0)==initial);
// On est au debut d'un cycle d'une seconde !!!
initial = time(0);
start();
do {
dummy+=2;
}
while(time(0)==initial);
final=time(0);
stop();
// INFOS("fine grained time : "<< get_elapsed_time_in_second());
// INFOS("coarse grained time : "<< final-initial);
_frequency=_frequency*get_elapsed_time_in_second()/double(final-initial);
/// INFOS("CPU frequency : "<< _frequency);
}
void add_get_click( void ){
_nb_sample++;
_counted_clicks[get_click()]++;
fill_history_clicks();
}
void dump_statistics(string filemane){
ofstream outfile (filemane.c_str(),ios::out) ;
std::map<unsigned long long , unsigned long long>::iterator itr;
for(itr=_counted_clicks.begin() ; itr!=_counted_clicks.end() ; itr++)
{
outfile << (*itr).first << " " << (*itr).second << endl ;
}
outfile.close();
}
void dump_history(string filemane){
ofstream outfile (filemane.c_str(),ios::out) ;
for(int i=0 ; i<_history_mean_clicks.size() ; i++)
{
outfile << i << " "
<< _history_mean_clicks[i] << " "
<< _history_shortest_clicks[i] << " "
<< _history_most_occured_clicks[i] << endl ;
}
outfile.close();
}
double get_mean_clicks( void ){
std::map<unsigned long long,unsigned long long>::iterator itr;
unsigned long long mean_clicks=0;
for(itr=_counted_clicks.begin() ; itr!=_counted_clicks.end() ; itr++)
{
mean_clicks+=(*itr).second*(*itr).first;
}
return mean_clicks/double(_nb_sample);
}
double get_shortest_clicks( void ){
return double((*_counted_clicks.begin()).first);
}
void fill_history_clicks( void ){
_history_mean_clicks.push_back(get_mean_clicks());
_history_shortest_clicks.push_back(get_shortest_clicks());
_history_most_occured_clicks.push_back(get_most_occured_clicks());
}
double get_most_occured_clicks( void ){
unsigned long long moc=0;
unsigned long long max_occurence=0;
std::map<unsigned long long,unsigned long long>::iterator itr;
for(itr=_counted_clicks.begin() ; itr!=_counted_clicks.end() ; itr++)
{
if (max_occurence<=(*itr).second){
max_occurence=(*itr).second;
moc=(*itr).first;
}
}
return double(moc);
}
void clear( void )
{
_counted_clicks.clear();
_history_mean_clicks.clear();
_history_shortest_clicks.clear();
_history_most_occured_clicks.clear();
_nb_sample=0;
}
private :
union
{
unsigned long int n32[2] ;
unsigned long long n64 ;
} _click_start;
union
{
unsigned long int n32[2] ;
unsigned long long n64 ;
} _click_stop;
double _frequency ;
map<unsigned long long,unsigned long long> _counted_clicks;
vector<double> _history_mean_clicks;
vector<double> _history_shortest_clicks;
vector<double> _history_most_occured_clicks;
unsigned long long _nb_sample;
};
#endif
| Unknown |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/generic_bench/static/bench_static.hh | .hh | 2,278 | 81 | //=====================================================
// File : bench_static.hh
// Author : L. Plagne <laurent.plagne@edf.fr)>
// Copyright (C) EDF R&D, lun sep 30 14:23:16 CEST 2002
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#ifndef BENCH_STATIC_HH
#define BENCH_STATIC_HH
#include "btl.hh"
#include "bench_parameter.hh"
#include <iostream>
#include "utilities.h"
#include "xy_file.hh"
#include "static/static_size_generator.hh"
#include "timers/portable_perf_analyzer.hh"
// #include "timers/mixed_perf_analyzer.hh"
// #include "timers/x86_perf_analyzer.hh"
using namespace std;
template <template<class> class Perf_Analyzer, template<class> class Action, template<class,int> class Interface>
BTL_DONT_INLINE void bench_static(void)
{
if (BtlConfig::skipAction(Action<Interface<REAL_TYPE,10> >::name()))
return;
string filename = "bench_" + Action<Interface<REAL_TYPE,10> >::name() + ".dat";
INFOS("starting " << filename);
const int max_size = TINY_MV_MAX_SIZE;
std::vector<double> tab_mflops;
std::vector<double> tab_sizes;
static_size_generator<max_size,Perf_Analyzer,Action,Interface>::go(tab_sizes,tab_mflops);
dump_xy_file(tab_sizes,tab_mflops,filename);
}
// default Perf Analyzer
template <template<class> class Action, template<class,int> class Interface>
BTL_DONT_INLINE void bench_static(void)
{
bench_static<Portable_Perf_Analyzer,Action,Interface>();
//bench_static<Mixed_Perf_Analyzer,Action,Interface>();
//bench_static<X86_Perf_Analyzer,Action,Interface>();
}
#endif
| Unknown |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/gmm/main.cpp | .cpp | 2,113 | 52 | //=====================================================
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#include "utilities.h"
#include "gmm_interface.hh"
#include "bench.hh"
#include "basic_actions.hh"
#include "action_hessenberg.hh"
#include "action_partial_lu.hh"
BTL_MAIN;
int main()
{
bench<Action_axpy<gmm_interface<REAL_TYPE> > >(MIN_AXPY,MAX_AXPY,NB_POINT);
bench<Action_axpby<gmm_interface<REAL_TYPE> > >(MIN_AXPY,MAX_AXPY,NB_POINT);
bench<Action_matrix_vector_product<gmm_interface<REAL_TYPE> > >(MIN_MV,MAX_MV,NB_POINT);
bench<Action_atv_product<gmm_interface<REAL_TYPE> > >(MIN_MV,MAX_MV,NB_POINT);
bench<Action_matrix_matrix_product<gmm_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
// bench<Action_ata_product<gmm_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
// bench<Action_aat_product<gmm_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
bench<Action_trisolve<gmm_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
//bench<Action_lu_solve<blitz_LU_solve_interface<REAL_TYPE> > >(MIN_LU,MAX_LU,NB_POINT);
bench<Action_partial_lu<gmm_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
bench<Action_hessenberg<gmm_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
bench<Action_tridiagonalization<gmm_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/gmm/gmm_interface.hh | .hh | 4,174 | 145 | //=====================================================
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#ifndef GMM_INTERFACE_HH
#define GMM_INTERFACE_HH
#include <gmm/gmm.h>
#include <vector>
using namespace gmm;
template<class real>
class gmm_interface {
public :
typedef real real_type ;
typedef std::vector<real> stl_vector;
typedef std::vector<stl_vector > stl_matrix;
typedef gmm::dense_matrix<real> gene_matrix;
typedef stl_vector gene_vector;
static inline std::string name( void )
{
return "gmm";
}
static void free_matrix(gene_matrix & A, int N){
return ;
}
static void free_vector(gene_vector & B){
return ;
}
static inline void matrix_from_stl(gene_matrix & A, stl_matrix & A_stl){
A.resize(A_stl[0].size(),A_stl.size());
for (int j=0; j<A_stl.size() ; j++){
for (int i=0; i<A_stl[j].size() ; i++){
A(i,j) = A_stl[j][i];
}
}
}
static inline void vector_from_stl(gene_vector & B, stl_vector & B_stl){
B = B_stl;
}
static inline void vector_to_stl(gene_vector & B, stl_vector & B_stl){
B_stl = B;
}
static inline void matrix_to_stl(gene_matrix & A, stl_matrix & A_stl){
int N=A_stl.size();
for (int j=0;j<N;j++){
A_stl[j].resize(N);
for (int i=0;i<N;i++){
A_stl[j][i] = A(i,j);
}
}
}
static inline void matrix_matrix_product(const gene_matrix & A, const gene_matrix & B, gene_matrix & X, int N){
gmm::mult(A,B, X);
}
static inline void transposed_matrix_matrix_product(const gene_matrix & A, const gene_matrix & B, gene_matrix & X, int N){
gmm::mult(gmm::transposed(A),gmm::transposed(B), X);
}
static inline void ata_product(const gene_matrix & A, gene_matrix & X, int N){
gmm::mult(gmm::transposed(A),A, X);
}
static inline void aat_product(const gene_matrix & A, gene_matrix & X, int N){
gmm::mult(A,gmm::transposed(A), X);
}
static inline void matrix_vector_product(gene_matrix & A, gene_vector & B, gene_vector & X, int N){
gmm::mult(A,B,X);
}
static inline void atv_product(gene_matrix & A, gene_vector & B, gene_vector & X, int N){
gmm::mult(gmm::transposed(A),B,X);
}
static inline void axpy(const real coef, const gene_vector & X, gene_vector & Y, int N){
gmm::add(gmm::scaled(X,coef), Y);
}
static inline void axpby(real a, const gene_vector & X, real b, gene_vector & Y, int N){
gmm::add(gmm::scaled(X,a), gmm::scaled(Y,b), Y);
}
static inline void copy_matrix(const gene_matrix & source, gene_matrix & cible, int N){
gmm::copy(source,cible);
}
static inline void copy_vector(const gene_vector & source, gene_vector & cible, int N){
gmm::copy(source,cible);
}
static inline void trisolve_lower(const gene_matrix & L, const gene_vector& B, gene_vector & X, int N){
gmm::copy(B,X);
gmm::lower_tri_solve(L, X, false);
}
static inline void partial_lu_decomp(const gene_matrix & X, gene_matrix & R, int N){
gmm::copy(X,R);
std::vector<int> ipvt(N);
gmm::lu_factor(R, ipvt);
}
static inline void hessenberg(const gene_matrix & X, gene_matrix & R, int N){
gmm::copy(X,R);
gmm::Hessenberg_reduction(R,X,false);
}
static inline void tridiagonalization(const gene_matrix & X, gene_matrix & R, int N){
gmm::copy(X,R);
gmm::Householder_tridiagonalization(R,X,false);
}
};
#endif
| Unknown |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/gmm/gmm_LU_solve_interface.hh | .hh | 5,364 | 193 | //=====================================================
// File : blitz_LU_solve_interface.hh
// Author : L. Plagne <laurent.plagne@edf.fr)>
// Copyright (C) EDF R&D, lun sep 30 14:23:31 CEST 2002
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#ifndef BLITZ_LU_SOLVE_INTERFACE_HH
#define BLITZ_LU_SOLVE_INTERFACE_HH
#include "blitz/array.h"
#include <vector>
BZ_USING_NAMESPACE(blitz)
template<class real>
class blitz_LU_solve_interface : public blitz_interface<real>
{
public :
typedef typename blitz_interface<real>::gene_matrix gene_matrix;
typedef typename blitz_interface<real>::gene_vector gene_vector;
typedef blitz::Array<int,1> Pivot_Vector;
inline static void new_Pivot_Vector(Pivot_Vector & pivot,int N)
{
pivot.resize(N);
}
inline static void free_Pivot_Vector(Pivot_Vector & pivot)
{
return;
}
static inline real matrix_vector_product_sliced(const gene_matrix & A, gene_vector B, int row, int col_start, int col_end)
{
real somme=0.;
for (int j=col_start ; j<col_end+1 ; j++){
somme+=A(row,j)*B(j);
}
return somme;
}
static inline real matrix_matrix_product_sliced(gene_matrix & A, int row, int col_start, int col_end, gene_matrix & B, int row_shift, int col )
{
real somme=0.;
for (int j=col_start ; j<col_end+1 ; j++){
somme+=A(row,j)*B(j+row_shift,col);
}
return somme;
}
inline static void LU_factor(gene_matrix & LU, Pivot_Vector & pivot, int N)
{
ASSERT( LU.rows()==LU.cols() ) ;
int index_max = 0 ;
real big = 0. ;
real theSum = 0. ;
real dum = 0. ;
// Get the implicit scaling information :
gene_vector ImplicitScaling( N ) ;
for( int i=0; i<N; i++ ) {
big = 0. ;
for( int j=0; j<N; j++ ) {
if( abs( LU( i, j ) )>=big ) big = abs( LU( i, j ) ) ;
}
if( big==0. ) {
INFOS( "blitz_LU_factor::Singular matrix" ) ;
exit( 0 ) ;
}
ImplicitScaling( i ) = 1./big ;
}
// Loop over columns of Crout's method :
for( int j=0; j<N; j++ ) {
for( int i=0; i<j; i++ ) {
theSum = LU( i, j ) ;
theSum -= matrix_matrix_product_sliced(LU, i, 0, i-1, LU, 0, j) ;
// theSum -= sum( LU( i, Range( fromStart, i-1 ) )*LU( Range( fromStart, i-1 ), j ) ) ;
LU( i, j ) = theSum ;
}
// Search for the largest pivot element :
big = 0. ;
for( int i=j; i<N; i++ ) {
theSum = LU( i, j ) ;
theSum -= matrix_matrix_product_sliced(LU, i, 0, j-1, LU, 0, j) ;
// theSum -= sum( LU( i, Range( fromStart, j-1 ) )*LU( Range( fromStart, j-1 ), j ) ) ;
LU( i, j ) = theSum ;
if( (ImplicitScaling( i )*abs( theSum ))>=big ) {
dum = ImplicitScaling( i )*abs( theSum ) ;
big = dum ;
index_max = i ;
}
}
// Interchanging rows and the scale factor :
if( j!=index_max ) {
for( int k=0; k<N; k++ ) {
dum = LU( index_max, k ) ;
LU( index_max, k ) = LU( j, k ) ;
LU( j, k ) = dum ;
}
ImplicitScaling( index_max ) = ImplicitScaling( j ) ;
}
pivot( j ) = index_max ;
if ( LU( j, j )==0. ) LU( j, j ) = 1.e-20 ;
// Divide by the pivot element :
if( j<N ) {
dum = 1./LU( j, j ) ;
for( int i=j+1; i<N; i++ ) LU( i, j ) *= dum ;
}
}
}
inline static void LU_solve(const gene_matrix & LU, const Pivot_Vector pivot, gene_vector &B, gene_vector X, int N)
{
// Pour conserver le meme header, on travaille sur X, copie du second-membre B
X = B.copy() ;
ASSERT( LU.rows()==LU.cols() ) ;
firstIndex indI ;
// Forward substitution :
int ii = 0 ;
real theSum = 0. ;
for( int i=0; i<N; i++ ) {
int ip = pivot( i ) ;
theSum = X( ip ) ;
// theSum = B( ip ) ;
X( ip ) = X( i ) ;
// B( ip ) = B( i ) ;
if( ii ) {
theSum -= matrix_vector_product_sliced(LU, X, i, ii-1, i-1) ;
// theSum -= sum( LU( i, Range( ii-1, i-1 ) )*X( Range( ii-1, i-1 ) ) ) ;
// theSum -= sum( LU( i, Range( ii-1, i-1 ) )*B( Range( ii-1, i-1 ) ) ) ;
} else if( theSum ) {
ii = i+1 ;
}
X( i ) = theSum ;
// B( i ) = theSum ;
}
// Backsubstitution :
for( int i=N-1; i>=0; i-- ) {
theSum = X( i ) ;
// theSum = B( i ) ;
theSum -= matrix_vector_product_sliced(LU, X, i, i+1, N) ;
// theSum -= sum( LU( i, Range( i+1, toEnd ) )*X( Range( i+1, toEnd ) ) ) ;
// theSum -= sum( LU( i, Range( i+1, toEnd ) )*B( Range( i+1, toEnd ) ) ) ;
// Store a component of the solution vector :
X( i ) = theSum/LU( i, i ) ;
// B( i ) = theSum/LU( i, i ) ;
}
}
};
#endif
| Unknown |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/ublas/ublas_interface.hh | .hh | 4,342 | 142 | //=====================================================
// File : ublas_interface.hh
// Author : L. Plagne <laurent.plagne@edf.fr)>
// Copyright (C) EDF R&D, lun sep 30 14:23:27 CEST 2002
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#ifndef UBLAS_INTERFACE_HH
#define UBLAS_INTERFACE_HH
#include <boost/numeric/ublas/vector.hpp>
#include <boost/numeric/ublas/matrix.hpp>
#include <boost/numeric/ublas/io.hpp>
#include <boost/numeric/ublas/triangular.hpp>
using namespace boost::numeric;
template <class real>
class ublas_interface{
public :
typedef real real_type ;
typedef std::vector<real> stl_vector;
typedef std::vector<stl_vector> stl_matrix;
typedef typename boost::numeric::ublas::matrix<real,boost::numeric::ublas::column_major> gene_matrix;
typedef typename boost::numeric::ublas::vector<real> gene_vector;
static inline std::string name( void ) { return "ublas"; }
static void free_matrix(gene_matrix & A, int N) {}
static void free_vector(gene_vector & B) {}
static inline void matrix_from_stl(gene_matrix & A, stl_matrix & A_stl){
A.resize(A_stl.size(),A_stl[0].size());
for (int j=0; j<A_stl.size() ; j++)
for (int i=0; i<A_stl[j].size() ; i++)
A(i,j)=A_stl[j][i];
}
static inline void vector_from_stl(gene_vector & B, stl_vector & B_stl){
B.resize(B_stl.size());
for (int i=0; i<B_stl.size() ; i++)
B(i)=B_stl[i];
}
static inline void vector_to_stl(gene_vector & B, stl_vector & B_stl){
for (int i=0; i<B_stl.size() ; i++)
B_stl[i]=B(i);
}
static inline void matrix_to_stl(gene_matrix & A, stl_matrix & A_stl){
int N=A_stl.size();
for (int j=0;j<N;j++)
{
A_stl[j].resize(N);
for (int i=0;i<N;i++)
A_stl[j][i]=A(i,j);
}
}
static inline void copy_vector(const gene_vector & source, gene_vector & cible, int N){
for (int i=0;i<N;i++){
cible(i) = source(i);
}
}
static inline void copy_matrix(const gene_matrix & source, gene_matrix & cible, int N){
for (int i=0;i<N;i++){
for (int j=0;j<N;j++){
cible(i,j) = source(i,j);
}
}
}
static inline void matrix_vector_product_slow(gene_matrix & A, gene_vector & B, gene_vector & X, int N){
X = prod(A,B);
}
static inline void matrix_matrix_product_slow(gene_matrix & A, gene_matrix & B, gene_matrix & X, int N){
X = prod(A,B);
}
static inline void axpy_slow(const real coef, const gene_vector & X, gene_vector & Y, int N){
Y+=coef*X;
}
// alias free assignements
static inline void matrix_vector_product(gene_matrix & A, gene_vector & B, gene_vector & X, int N){
X.assign(prod(A,B));
}
static inline void atv_product(gene_matrix & A, gene_vector & B, gene_vector & X, int N){
X.assign(prod(trans(A),B));
}
static inline void matrix_matrix_product(gene_matrix & A, gene_matrix & B, gene_matrix & X, int N){
X.assign(prod(A,B));
}
static inline void axpy(const real coef, const gene_vector & X, gene_vector & Y, int N){
Y.plus_assign(coef*X);
}
static inline void axpby(real a, const gene_vector & X, real b, gene_vector & Y, int N){
Y = a*X + b*Y;
}
static inline void ata_product(gene_matrix & A, gene_matrix & X, int N){
// X = prod(trans(A),A);
X.assign(prod(trans(A),A));
}
static inline void aat_product(gene_matrix & A, gene_matrix & X, int N){
// X = prod(A,trans(A));
X.assign(prod(A,trans(A)));
}
static inline void trisolve_lower(const gene_matrix & L, const gene_vector& B, gene_vector & X, int N){
X = solve(L, B, ublas::lower_tag ());
}
};
#endif
| Unknown |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/ublas/main.cpp | .cpp | 1,785 | 45 | //=====================================================
// File : main.cpp
// Author : L. Plagne <laurent.plagne@edf.fr)>
// Copyright (C) EDF R&D, lun sep 30 14:23:27 CEST 2002
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#include "utilities.h"
#include "ublas_interface.hh"
#include "bench.hh"
#include "basic_actions.hh"
BTL_MAIN;
int main()
{
bench<Action_axpy<ublas_interface<REAL_TYPE> > >(MIN_AXPY,MAX_AXPY,NB_POINT);
bench<Action_axpby<ublas_interface<REAL_TYPE> > >(MIN_AXPY,MAX_AXPY,NB_POINT);
bench<Action_matrix_vector_product<ublas_interface<REAL_TYPE> > >(MIN_MV,MAX_MV,NB_POINT);
bench<Action_atv_product<ublas_interface<REAL_TYPE> > >(MIN_MV,MAX_MV,NB_POINT);
bench<Action_matrix_matrix_product<ublas_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
// bench<Action_ata_product<ublas_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
// bench<Action_aat_product<ublas_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
bench<Action_trisolve<ublas_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/tvmet/tvmet_interface.hh | .hh | 3,017 | 105 | //=====================================================
// File : tvmet_interface.hh
// Author : L. Plagne <laurent.plagne@edf.fr)>
// Copyright (C) EDF R&D, lun sep 30 14:23:30 CEST 2002
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#ifndef TVMET_INTERFACE_HH
#define TVMET_INTERFACE_HH
#include <tvmet/tvmet.h>
#include <tvmet/Vector.h>
#include <tvmet/Matrix.h>
#include <vector>
using namespace tvmet;
template<class real, int SIZE>
class tvmet_interface{
public :
typedef real real_type ;
typedef std::vector<real> stl_vector;
typedef std::vector<stl_vector > stl_matrix;
typedef Vector<real,SIZE> gene_vector;
typedef Matrix<real,SIZE,SIZE> gene_matrix;
static inline std::string name() { return "tiny_tvmet"; }
static void free_matrix(gene_matrix & A, int N){}
static void free_vector(gene_vector & B){}
static inline void matrix_from_stl(gene_matrix & A, stl_matrix & A_stl){
for (int j=0; j<A_stl.size() ; j++)
for (int i=0; i<A_stl[j].size() ; i++)
A(i,j) = A_stl[j][i];
}
static inline void vector_from_stl(gene_vector & B, stl_vector & B_stl){
for (int i=0; i<B_stl.size() ; i++)
B[i]=B_stl[i];
}
static inline void vector_to_stl(gene_vector & B, stl_vector & B_stl){
for (int i=0; i<B_stl.size() ; i++){
B_stl[i]=B[i];
}
}
static inline void matrix_to_stl(gene_matrix & A, stl_matrix & A_stl){
int N = A_stl.size();
for (int j=0;j<N;j++){
A_stl[j].resize(N);
for (int i=0;i<N;i++)
A_stl[j][i] = A(i,j);
}
}
static inline void copy_matrix(const gene_matrix & source, gene_matrix & cible, int N){
cible = source;
}
static inline void copy_vector(const gene_vector & source, gene_vector & cible, int N){
cible = source;
}
static inline void matrix_matrix_product(const gene_matrix & A, const gene_matrix & B, gene_matrix & X, int N){
X = prod(A,B);
}
static inline void matrix_vector_product(gene_matrix & A, gene_vector & B, gene_vector & X, int N){
X = prod(A,B);
}
static inline void atv_product(gene_matrix & A, gene_vector & B, gene_vector & X, int N){
X = prod(trans(A),B);
}
static inline void axpy(const real coef, const gene_vector & X, gene_vector & Y, int N){
Y+=coef*X;
}
};
#endif
| Unknown |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/tvmet/main.cpp | .cpp | 1,460 | 41 | //=====================================================
// File : main.cpp
// Author : L. Plagne <laurent.plagne@edf.fr)>
// Copyright (C) EDF R&D, lun sep 30 14:23:30 CEST 2002
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#include "utilities.h"
#include "tvmet_interface.hh"
#include "static/bench_static.hh"
#include "action_matrix_vector_product.hh"
#include "action_matrix_matrix_product.hh"
#include "action_atv_product.hh"
#include "action_axpy.hh"
BTL_MAIN;
int main()
{
bench_static<Action_axpy,tvmet_interface>();
bench_static<Action_matrix_matrix_product,tvmet_interface>();
bench_static<Action_matrix_vector_product,tvmet_interface>();
bench_static<Action_atv_product,tvmet_interface>();
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/tensors/main_vecmat.cpp | .cpp | 624 | 22 | //=====================================================
// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
//=====================================================
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
//
#include "utilities.h"
#include "tensor_interface.hh"
#include "bench.hh"
#include "basic_actions.hh"
BTL_MAIN;
int main()
{
bench<Action_matrix_vector_product<tensor_interface<REAL_TYPE> > >(MIN_MV,MAX_MV,NB_POINT);
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/tensors/main_linear.cpp | .cpp | 671 | 24 | // This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
#include "utilities.h"
#include "tensor_interface.hh"
#include "bench.hh"
#include "basic_actions.hh"
BTL_MAIN;
int main()
{
bench<Action_axpy<tensor_interface<REAL_TYPE> > >(MIN_AXPY,MAX_AXPY,NB_POINT);
bench<Action_axpby<tensor_interface<REAL_TYPE> > >(MIN_AXPY,MAX_AXPY,NB_POINT);
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/tensors/main_matmat.cpp | .cpp | 624 | 22 | //=====================================================
// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
//=====================================================
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
//
#include "utilities.h"
#include "tensor_interface.hh"
#include "bench.hh"
#include "basic_actions.hh"
BTL_MAIN;
int main()
{
bench<Action_matrix_matrix_product<tensor_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/tensors/tensor_interface.hh | .hh | 3,190 | 106 | //=====================================================
// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
//=====================================================
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
//
#ifndef TENSOR_INTERFACE_HH
#define TENSOR_INTERFACE_HH
#include <unsupported/Eigen/CXX11/Tensor>
#include <vector>
#include "btl.hh"
using namespace Eigen;
template<class real>
class tensor_interface
{
public :
typedef real real_type;
typedef typename Eigen::Tensor<real,2>::Index Index;
typedef std::vector<real> stl_vector;
typedef std::vector<stl_vector> stl_matrix;
typedef Eigen::Tensor<real,2> gene_matrix;
typedef Eigen::Tensor<real,1> gene_vector;
static inline std::string name( void )
{
return EIGEN_MAKESTRING(BTL_PREFIX);
}
static void free_matrix(gene_matrix & /*A*/, int /*N*/) {}
static void free_vector(gene_vector & /*B*/) {}
static BTL_DONT_INLINE void matrix_from_stl(gene_matrix & A, stl_matrix & A_stl){
A.resize(Eigen::array<Index,2>(A_stl[0].size(), A_stl.size()));
for (unsigned int j=0; j<A_stl.size() ; j++){
for (unsigned int i=0; i<A_stl[j].size() ; i++){
A.coeffRef(Eigen::array<Index,2>(i,j)) = A_stl[j][i];
}
}
}
static BTL_DONT_INLINE void vector_from_stl(gene_vector & B, stl_vector & B_stl){
B.resize(B_stl.size());
for (unsigned int i=0; i<B_stl.size() ; i++){
B.coeffRef(i) = B_stl[i];
}
}
static BTL_DONT_INLINE void vector_to_stl(gene_vector & B, stl_vector & B_stl){
for (unsigned int i=0; i<B_stl.size() ; i++){
B_stl[i] = B.coeff(i);
}
}
static BTL_DONT_INLINE void matrix_to_stl(gene_matrix & A, stl_matrix & A_stl){
int N=A_stl.size();
for (int j=0;j<N;j++){
A_stl[j].resize(N);
for (int i=0;i<N;i++){
A_stl[j][i] = A.coeff(Eigen::array<Index,2>(i,j));
}
}
}
static inline void matrix_matrix_product(const gene_matrix & A, const gene_matrix & B, gene_matrix & X, int /*N*/){
typedef typename Eigen::Tensor<real_type, 1>::DimensionPair DimPair;
const Eigen::array<DimPair, 1> dims(DimPair(1, 0));
X/*.noalias()*/ = A.contract(B, dims);
}
static inline void matrix_vector_product(const gene_matrix & A, const gene_vector & B, gene_vector & X, int /*N*/){
typedef typename Eigen::Tensor<real_type, 1>::DimensionPair DimPair;
const Eigen::array<DimPair, 1> dims(DimPair(1, 0));
X/*.noalias()*/ = A.contract(B, dims);
}
static inline void axpy(real coef, const gene_vector & X, gene_vector & Y, int /*N*/){
Y += X.constant(coef) * X;
}
static inline void axpby(real a, const gene_vector & X, real b, gene_vector & Y, int /*N*/){
Y = X.constant(a)*X + Y.constant(b)*Y;
}
static EIGEN_DONT_INLINE void copy_matrix(const gene_matrix & source, gene_matrix & cible, int /*N*/){
cible = source;
}
static EIGEN_DONT_INLINE void copy_vector(const gene_vector & source, gene_vector & cible, int /*N*/){
cible = source;
}
};
#endif
| Unknown |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/BLAS/blas_interface_impl.hh | .hh | 4,811 | 148 |
#define BLAS_FUNC(NAME) CAT(CAT(SCALAR_PREFIX,NAME),_)
template<> class blas_interface<SCALAR> : public c_interface_base<SCALAR>
{
public :
static SCALAR fone;
static SCALAR fzero;
static inline std::string name()
{
return MAKE_STRING(CBLASNAME);
}
static inline void matrix_vector_product(gene_matrix & A, gene_vector & B, gene_vector & X, int N){
BLAS_FUNC(gemv)(¬rans,&N,&N,&fone,A,&N,B,&intone,&fzero,X,&intone);
}
static inline void symv(gene_matrix & A, gene_vector & B, gene_vector & X, int N){
BLAS_FUNC(symv)(&lower, &N,&fone,A,&N,B,&intone,&fzero,X,&intone);
}
static inline void syr2(gene_matrix & A, gene_vector & B, gene_vector & X, int N){
BLAS_FUNC(syr2)(&lower,&N,&fone,B,&intone,X,&intone,A,&N);
}
static inline void ger(gene_matrix & A, gene_vector & X, gene_vector & Y, int N){
BLAS_FUNC(ger)(&N,&N,&fone,X,&intone,Y,&intone,A,&N);
}
static inline void rot(gene_vector & A, gene_vector & B, SCALAR c, SCALAR s, int N){
BLAS_FUNC(rot)(&N,A,&intone,B,&intone,&c,&s);
}
static inline void atv_product(gene_matrix & A, gene_vector & B, gene_vector & X, int N){
BLAS_FUNC(gemv)(&trans,&N,&N,&fone,A,&N,B,&intone,&fzero,X,&intone);
}
static inline void matrix_matrix_product(gene_matrix & A, gene_matrix & B, gene_matrix & X, int N){
BLAS_FUNC(gemm)(¬rans,¬rans,&N,&N,&N,&fone,A,&N,B,&N,&fzero,X,&N);
}
static inline void transposed_matrix_matrix_product(gene_matrix & A, gene_matrix & B, gene_matrix & X, int N){
BLAS_FUNC(gemm)(¬rans,¬rans,&N,&N,&N,&fone,A,&N,B,&N,&fzero,X,&N);
}
// static inline void ata_product(gene_matrix & A, gene_matrix & X, int N){
// ssyrk_(&lower,&trans,&N,&N,&fone,A,&N,&fzero,X,&N);
// }
static inline void aat_product(gene_matrix & A, gene_matrix & X, int N){
BLAS_FUNC(syrk)(&lower,¬rans,&N,&N,&fone,A,&N,&fzero,X,&N);
}
static inline void axpy(SCALAR coef, const gene_vector & X, gene_vector & Y, int N){
BLAS_FUNC(axpy)(&N,&coef,X,&intone,Y,&intone);
}
static inline void axpby(SCALAR a, const gene_vector & X, SCALAR b, gene_vector & Y, int N){
BLAS_FUNC(scal)(&N,&b,Y,&intone);
BLAS_FUNC(axpy)(&N,&a,X,&intone,Y,&intone);
}
static inline void cholesky(const gene_matrix & X, gene_matrix & C, int N){
int N2 = N*N;
BLAS_FUNC(copy)(&N2, X, &intone, C, &intone);
char uplo = 'L';
int info = 0;
BLAS_FUNC(potrf)(&uplo, &N, C, &N, &info);
if(info!=0) std::cerr << "potrf_ error " << info << "\n";
}
static inline void partial_lu_decomp(const gene_matrix & X, gene_matrix & C, int N){
int N2 = N*N;
BLAS_FUNC(copy)(&N2, X, &intone, C, &intone);
int info = 0;
int * ipiv = (int*)alloca(sizeof(int)*N);
BLAS_FUNC(getrf)(&N, &N, C, &N, ipiv, &info);
if(info!=0) std::cerr << "getrf_ error " << info << "\n";
}
static inline void trisolve_lower(const gene_matrix & L, const gene_vector& B, gene_vector & X, int N){
BLAS_FUNC(copy)(&N, B, &intone, X, &intone);
BLAS_FUNC(trsv)(&lower, ¬rans, &nonunit, &N, L, &N, X, &intone);
}
static inline void trisolve_lower_matrix(const gene_matrix & L, const gene_matrix& B, gene_matrix & X, int N){
BLAS_FUNC(copy)(&N, B, &intone, X, &intone);
BLAS_FUNC(trsm)(&right, &lower, ¬rans, &nonunit, &N, &N, &fone, L, &N, X, &N);
}
static inline void trmm(gene_matrix & A, gene_matrix & B, gene_matrix & /*X*/, int N){
BLAS_FUNC(trmm)(&left, &lower, ¬rans,&nonunit, &N,&N,&fone,A,&N,B,&N);
}
#ifdef HAS_LAPACK
static inline void lu_decomp(const gene_matrix & X, gene_matrix & C, int N){
int N2 = N*N;
BLAS_FUNC(copy)(&N2, X, &intone, C, &intone);
int info = 0;
int * ipiv = (int*)alloca(sizeof(int)*N);
int * jpiv = (int*)alloca(sizeof(int)*N);
BLAS_FUNC(getc2)(&N, C, &N, ipiv, jpiv, &info);
}
static inline void hessenberg(const gene_matrix & X, gene_matrix & C, int N){
{
int N2 = N*N;
int inc = 1;
BLAS_FUNC(copy)(&N2, X, &inc, C, &inc);
}
int info = 0;
int ilo = 1;
int ihi = N;
int bsize = 64;
int worksize = N*bsize;
SCALAR* d = new SCALAR[N+worksize];
BLAS_FUNC(gehrd)(&N, &ilo, &ihi, C, &N, d, d+N, &worksize, &info);
delete[] d;
}
static inline void tridiagonalization(const gene_matrix & X, gene_matrix & C, int N){
{
int N2 = N*N;
int inc = 1;
BLAS_FUNC(copy)(&N2, X, &inc, C, &inc);
}
char uplo = 'U';
int info = 0;
int bsize = 64;
int worksize = N*bsize;
SCALAR* d = new SCALAR[3*N+worksize];
BLAS_FUNC(sytrd)(&uplo, &N, C, &N, d, d+N, d+2*N, d+3*N, &worksize, &info);
delete[] d;
}
#endif // HAS_LAPACK
};
SCALAR blas_interface<SCALAR>::fone = SCALAR(1);
SCALAR blas_interface<SCALAR>::fzero = SCALAR(0);
| Unknown |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/BLAS/blas.h | .h | 35,158 | 676 | #ifndef BLAS_H
#define BLAS_H
#define BLASFUNC(FUNC) FUNC##_
#ifdef __WIN64__
typedef long long BLASLONG;
typedef unsigned long long BLASULONG;
#else
typedef long BLASLONG;
typedef unsigned long BLASULONG;
#endif
int BLASFUNC(xerbla)(const char *, int *info, int);
float BLASFUNC(sdot) (int *, float *, int *, float *, int *);
float BLASFUNC(sdsdot)(int *, float *, float *, int *, float *, int *);
double BLASFUNC(dsdot) (int *, float *, int *, float *, int *);
double BLASFUNC(ddot) (int *, double *, int *, double *, int *);
double BLASFUNC(qdot) (int *, double *, int *, double *, int *);
#if defined(F_INTERFACE_GFORT) && !defined(__64BIT__)
int BLASFUNC(cdotu) (int *, float * , int *, float *, int *);
int BLASFUNC(cdotc) (int *, float *, int *, float *, int *);
void BLASFUNC(zdotu) (double *, int *, double *, int *, double *, int *);
void BLASFUNC(zdotc) (double *, int *, double *, int *, double *, int *);
void BLASFUNC(xdotu) (double *, int *, double *, int *, double *, int *);
void BLASFUNC(xdotc) (double *, int *, double *, int *, double *, int *);
#elif defined(F_INTERFACE_F2C) || \
defined(F_INTERFACE_PGI) || \
defined(F_INTERFACE_GFORT) || \
(defined(F_INTERFACE_PATHSCALE) && defined(__64BIT__))
void BLASFUNC(cdotu) (float *, int *, float * , int *, float *, int *);
void BLASFUNC(cdotc) (float *, int *, float *, int *, float *, int *);
void BLASFUNC(zdotu) (double *, int *, double *, int *, double *, int *);
void BLASFUNC(zdotc) (double *, int *, double *, int *, double *, int *);
void BLASFUNC(xdotu) (double *, int *, double *, int *, double *, int *);
void BLASFUNC(xdotc) (double *, int *, double *, int *, double *, int *);
#else
std::complex<float> BLASFUNC(cdotu) (int *, float *, int *, float *, int *);
std::complex<float> BLASFUNC(cdotc) (int *, float *, int *, float *, int *);
std::complex<double> BLASFUNC(zdotu) (int *, double *, int *, double *, int *);
std::complex<double> BLASFUNC(zdotc) (int *, double *, int *, double *, int *);
double BLASFUNC(xdotu) (int *, double *, int *, double *, int *);
double BLASFUNC(xdotc) (int *, double *, int *, double *, int *);
#endif
int BLASFUNC(cdotuw) (int *, float *, int *, float *, int *, float*);
int BLASFUNC(cdotcw) (int *, float *, int *, float *, int *, float*);
int BLASFUNC(zdotuw) (int *, double *, int *, double *, int *, double*);
int BLASFUNC(zdotcw) (int *, double *, int *, double *, int *, double*);
int BLASFUNC(saxpy) (int *, float *, float *, int *, float *, int *);
int BLASFUNC(daxpy) (int *, double *, double *, int *, double *, int *);
int BLASFUNC(qaxpy) (int *, double *, double *, int *, double *, int *);
int BLASFUNC(caxpy) (int *, float *, float *, int *, float *, int *);
int BLASFUNC(zaxpy) (int *, double *, double *, int *, double *, int *);
int BLASFUNC(xaxpy) (int *, double *, double *, int *, double *, int *);
int BLASFUNC(caxpyc)(int *, float *, float *, int *, float *, int *);
int BLASFUNC(zaxpyc)(int *, double *, double *, int *, double *, int *);
int BLASFUNC(xaxpyc)(int *, double *, double *, int *, double *, int *);
int BLASFUNC(scopy) (int *, float *, int *, float *, int *);
int BLASFUNC(dcopy) (int *, double *, int *, double *, int *);
int BLASFUNC(qcopy) (int *, double *, int *, double *, int *);
int BLASFUNC(ccopy) (int *, float *, int *, float *, int *);
int BLASFUNC(zcopy) (int *, double *, int *, double *, int *);
int BLASFUNC(xcopy) (int *, double *, int *, double *, int *);
int BLASFUNC(sswap) (int *, float *, int *, float *, int *);
int BLASFUNC(dswap) (int *, double *, int *, double *, int *);
int BLASFUNC(qswap) (int *, double *, int *, double *, int *);
int BLASFUNC(cswap) (int *, float *, int *, float *, int *);
int BLASFUNC(zswap) (int *, double *, int *, double *, int *);
int BLASFUNC(xswap) (int *, double *, int *, double *, int *);
float BLASFUNC(sasum) (int *, float *, int *);
float BLASFUNC(scasum)(int *, float *, int *);
double BLASFUNC(dasum) (int *, double *, int *);
double BLASFUNC(qasum) (int *, double *, int *);
double BLASFUNC(dzasum)(int *, double *, int *);
double BLASFUNC(qxasum)(int *, double *, int *);
int BLASFUNC(isamax)(int *, float *, int *);
int BLASFUNC(idamax)(int *, double *, int *);
int BLASFUNC(iqamax)(int *, double *, int *);
int BLASFUNC(icamax)(int *, float *, int *);
int BLASFUNC(izamax)(int *, double *, int *);
int BLASFUNC(ixamax)(int *, double *, int *);
int BLASFUNC(ismax) (int *, float *, int *);
int BLASFUNC(idmax) (int *, double *, int *);
int BLASFUNC(iqmax) (int *, double *, int *);
int BLASFUNC(icmax) (int *, float *, int *);
int BLASFUNC(izmax) (int *, double *, int *);
int BLASFUNC(ixmax) (int *, double *, int *);
int BLASFUNC(isamin)(int *, float *, int *);
int BLASFUNC(idamin)(int *, double *, int *);
int BLASFUNC(iqamin)(int *, double *, int *);
int BLASFUNC(icamin)(int *, float *, int *);
int BLASFUNC(izamin)(int *, double *, int *);
int BLASFUNC(ixamin)(int *, double *, int *);
int BLASFUNC(ismin)(int *, float *, int *);
int BLASFUNC(idmin)(int *, double *, int *);
int BLASFUNC(iqmin)(int *, double *, int *);
int BLASFUNC(icmin)(int *, float *, int *);
int BLASFUNC(izmin)(int *, double *, int *);
int BLASFUNC(ixmin)(int *, double *, int *);
float BLASFUNC(samax) (int *, float *, int *);
double BLASFUNC(damax) (int *, double *, int *);
double BLASFUNC(qamax) (int *, double *, int *);
float BLASFUNC(scamax)(int *, float *, int *);
double BLASFUNC(dzamax)(int *, double *, int *);
double BLASFUNC(qxamax)(int *, double *, int *);
float BLASFUNC(samin) (int *, float *, int *);
double BLASFUNC(damin) (int *, double *, int *);
double BLASFUNC(qamin) (int *, double *, int *);
float BLASFUNC(scamin)(int *, float *, int *);
double BLASFUNC(dzamin)(int *, double *, int *);
double BLASFUNC(qxamin)(int *, double *, int *);
float BLASFUNC(smax) (int *, float *, int *);
double BLASFUNC(dmax) (int *, double *, int *);
double BLASFUNC(qmax) (int *, double *, int *);
float BLASFUNC(scmax) (int *, float *, int *);
double BLASFUNC(dzmax) (int *, double *, int *);
double BLASFUNC(qxmax) (int *, double *, int *);
float BLASFUNC(smin) (int *, float *, int *);
double BLASFUNC(dmin) (int *, double *, int *);
double BLASFUNC(qmin) (int *, double *, int *);
float BLASFUNC(scmin) (int *, float *, int *);
double BLASFUNC(dzmin) (int *, double *, int *);
double BLASFUNC(qxmin) (int *, double *, int *);
int BLASFUNC(sscal) (int *, float *, float *, int *);
int BLASFUNC(dscal) (int *, double *, double *, int *);
int BLASFUNC(qscal) (int *, double *, double *, int *);
int BLASFUNC(cscal) (int *, float *, float *, int *);
int BLASFUNC(zscal) (int *, double *, double *, int *);
int BLASFUNC(xscal) (int *, double *, double *, int *);
int BLASFUNC(csscal)(int *, float *, float *, int *);
int BLASFUNC(zdscal)(int *, double *, double *, int *);
int BLASFUNC(xqscal)(int *, double *, double *, int *);
float BLASFUNC(snrm2) (int *, float *, int *);
float BLASFUNC(scnrm2)(int *, float *, int *);
double BLASFUNC(dnrm2) (int *, double *, int *);
double BLASFUNC(qnrm2) (int *, double *, int *);
double BLASFUNC(dznrm2)(int *, double *, int *);
double BLASFUNC(qxnrm2)(int *, double *, int *);
int BLASFUNC(srot) (int *, float *, int *, float *, int *, float *, float *);
int BLASFUNC(drot) (int *, double *, int *, double *, int *, double *, double *);
int BLASFUNC(qrot) (int *, double *, int *, double *, int *, double *, double *);
int BLASFUNC(csrot) (int *, float *, int *, float *, int *, float *, float *);
int BLASFUNC(zdrot) (int *, double *, int *, double *, int *, double *, double *);
int BLASFUNC(xqrot) (int *, double *, int *, double *, int *, double *, double *);
int BLASFUNC(srotg) (float *, float *, float *, float *);
int BLASFUNC(drotg) (double *, double *, double *, double *);
int BLASFUNC(qrotg) (double *, double *, double *, double *);
int BLASFUNC(crotg) (float *, float *, float *, float *);
int BLASFUNC(zrotg) (double *, double *, double *, double *);
int BLASFUNC(xrotg) (double *, double *, double *, double *);
int BLASFUNC(srotmg)(float *, float *, float *, float *, float *);
int BLASFUNC(drotmg)(double *, double *, double *, double *, double *);
int BLASFUNC(srotm) (int *, float *, int *, float *, int *, float *);
int BLASFUNC(drotm) (int *, double *, int *, double *, int *, double *);
int BLASFUNC(qrotm) (int *, double *, int *, double *, int *, double *);
/* Level 2 routines */
int BLASFUNC(sger)(int *, int *, float *, float *, int *,
float *, int *, float *, int *);
int BLASFUNC(dger)(int *, int *, double *, double *, int *,
double *, int *, double *, int *);
int BLASFUNC(qger)(int *, int *, double *, double *, int *,
double *, int *, double *, int *);
int BLASFUNC(cgeru)(int *, int *, float *, float *, int *,
float *, int *, float *, int *);
int BLASFUNC(cgerc)(int *, int *, float *, float *, int *,
float *, int *, float *, int *);
int BLASFUNC(zgeru)(int *, int *, double *, double *, int *,
double *, int *, double *, int *);
int BLASFUNC(zgerc)(int *, int *, double *, double *, int *,
double *, int *, double *, int *);
int BLASFUNC(xgeru)(int *, int *, double *, double *, int *,
double *, int *, double *, int *);
int BLASFUNC(xgerc)(int *, int *, double *, double *, int *,
double *, int *, double *, int *);
int BLASFUNC(sgemv)(char *, int *, int *, float *, float *, int *,
float *, int *, float *, float *, int *);
int BLASFUNC(dgemv)(char *, int *, int *, double *, double *, int *,
double *, int *, double *, double *, int *);
int BLASFUNC(qgemv)(char *, int *, int *, double *, double *, int *,
double *, int *, double *, double *, int *);
int BLASFUNC(cgemv)(char *, int *, int *, float *, float *, int *,
float *, int *, float *, float *, int *);
int BLASFUNC(zgemv)(char *, int *, int *, double *, double *, int *,
double *, int *, double *, double *, int *);
int BLASFUNC(xgemv)(char *, int *, int *, double *, double *, int *,
double *, int *, double *, double *, int *);
int BLASFUNC(strsv) (char *, char *, char *, int *, float *, int *,
float *, int *);
int BLASFUNC(dtrsv) (char *, char *, char *, int *, double *, int *,
double *, int *);
int BLASFUNC(qtrsv) (char *, char *, char *, int *, double *, int *,
double *, int *);
int BLASFUNC(ctrsv) (char *, char *, char *, int *, float *, int *,
float *, int *);
int BLASFUNC(ztrsv) (char *, char *, char *, int *, double *, int *,
double *, int *);
int BLASFUNC(xtrsv) (char *, char *, char *, int *, double *, int *,
double *, int *);
int BLASFUNC(stpsv) (char *, char *, char *, int *, float *, float *, int *);
int BLASFUNC(dtpsv) (char *, char *, char *, int *, double *, double *, int *);
int BLASFUNC(qtpsv) (char *, char *, char *, int *, double *, double *, int *);
int BLASFUNC(ctpsv) (char *, char *, char *, int *, float *, float *, int *);
int BLASFUNC(ztpsv) (char *, char *, char *, int *, double *, double *, int *);
int BLASFUNC(xtpsv) (char *, char *, char *, int *, double *, double *, int *);
int BLASFUNC(strmv) (char *, char *, char *, int *, float *, int *,
float *, int *);
int BLASFUNC(dtrmv) (char *, char *, char *, int *, double *, int *,
double *, int *);
int BLASFUNC(qtrmv) (char *, char *, char *, int *, double *, int *,
double *, int *);
int BLASFUNC(ctrmv) (char *, char *, char *, int *, float *, int *,
float *, int *);
int BLASFUNC(ztrmv) (char *, char *, char *, int *, double *, int *,
double *, int *);
int BLASFUNC(xtrmv) (char *, char *, char *, int *, double *, int *,
double *, int *);
int BLASFUNC(stpmv) (char *, char *, char *, int *, float *, float *, int *);
int BLASFUNC(dtpmv) (char *, char *, char *, int *, double *, double *, int *);
int BLASFUNC(qtpmv) (char *, char *, char *, int *, double *, double *, int *);
int BLASFUNC(ctpmv) (char *, char *, char *, int *, float *, float *, int *);
int BLASFUNC(ztpmv) (char *, char *, char *, int *, double *, double *, int *);
int BLASFUNC(xtpmv) (char *, char *, char *, int *, double *, double *, int *);
int BLASFUNC(stbmv) (char *, char *, char *, int *, int *, float *, int *, float *, int *);
int BLASFUNC(dtbmv) (char *, char *, char *, int *, int *, double *, int *, double *, int *);
int BLASFUNC(qtbmv) (char *, char *, char *, int *, int *, double *, int *, double *, int *);
int BLASFUNC(ctbmv) (char *, char *, char *, int *, int *, float *, int *, float *, int *);
int BLASFUNC(ztbmv) (char *, char *, char *, int *, int *, double *, int *, double *, int *);
int BLASFUNC(xtbmv) (char *, char *, char *, int *, int *, double *, int *, double *, int *);
int BLASFUNC(stbsv) (char *, char *, char *, int *, int *, float *, int *, float *, int *);
int BLASFUNC(dtbsv) (char *, char *, char *, int *, int *, double *, int *, double *, int *);
int BLASFUNC(qtbsv) (char *, char *, char *, int *, int *, double *, int *, double *, int *);
int BLASFUNC(ctbsv) (char *, char *, char *, int *, int *, float *, int *, float *, int *);
int BLASFUNC(ztbsv) (char *, char *, char *, int *, int *, double *, int *, double *, int *);
int BLASFUNC(xtbsv) (char *, char *, char *, int *, int *, double *, int *, double *, int *);
int BLASFUNC(ssymv) (char *, int *, float *, float *, int *,
float *, int *, float *, float *, int *);
int BLASFUNC(dsymv) (char *, int *, double *, double *, int *,
double *, int *, double *, double *, int *);
int BLASFUNC(qsymv) (char *, int *, double *, double *, int *,
double *, int *, double *, double *, int *);
int BLASFUNC(csymv) (char *, int *, float *, float *, int *,
float *, int *, float *, float *, int *);
int BLASFUNC(zsymv) (char *, int *, double *, double *, int *,
double *, int *, double *, double *, int *);
int BLASFUNC(xsymv) (char *, int *, double *, double *, int *,
double *, int *, double *, double *, int *);
int BLASFUNC(sspmv) (char *, int *, float *, float *,
float *, int *, float *, float *, int *);
int BLASFUNC(dspmv) (char *, int *, double *, double *,
double *, int *, double *, double *, int *);
int BLASFUNC(qspmv) (char *, int *, double *, double *,
double *, int *, double *, double *, int *);
int BLASFUNC(cspmv) (char *, int *, float *, float *,
float *, int *, float *, float *, int *);
int BLASFUNC(zspmv) (char *, int *, double *, double *,
double *, int *, double *, double *, int *);
int BLASFUNC(xspmv) (char *, int *, double *, double *,
double *, int *, double *, double *, int *);
int BLASFUNC(ssyr) (char *, int *, float *, float *, int *,
float *, int *);
int BLASFUNC(dsyr) (char *, int *, double *, double *, int *,
double *, int *);
int BLASFUNC(qsyr) (char *, int *, double *, double *, int *,
double *, int *);
int BLASFUNC(csyr) (char *, int *, float *, float *, int *,
float *, int *);
int BLASFUNC(zsyr) (char *, int *, double *, double *, int *,
double *, int *);
int BLASFUNC(xsyr) (char *, int *, double *, double *, int *,
double *, int *);
int BLASFUNC(ssyr2) (char *, int *, float *,
float *, int *, float *, int *, float *, int *);
int BLASFUNC(dsyr2) (char *, int *, double *,
double *, int *, double *, int *, double *, int *);
int BLASFUNC(qsyr2) (char *, int *, double *,
double *, int *, double *, int *, double *, int *);
int BLASFUNC(csyr2) (char *, int *, float *,
float *, int *, float *, int *, float *, int *);
int BLASFUNC(zsyr2) (char *, int *, double *,
double *, int *, double *, int *, double *, int *);
int BLASFUNC(xsyr2) (char *, int *, double *,
double *, int *, double *, int *, double *, int *);
int BLASFUNC(sspr) (char *, int *, float *, float *, int *,
float *);
int BLASFUNC(dspr) (char *, int *, double *, double *, int *,
double *);
int BLASFUNC(qspr) (char *, int *, double *, double *, int *,
double *);
int BLASFUNC(cspr) (char *, int *, float *, float *, int *,
float *);
int BLASFUNC(zspr) (char *, int *, double *, double *, int *,
double *);
int BLASFUNC(xspr) (char *, int *, double *, double *, int *,
double *);
int BLASFUNC(sspr2) (char *, int *, float *,
float *, int *, float *, int *, float *);
int BLASFUNC(dspr2) (char *, int *, double *,
double *, int *, double *, int *, double *);
int BLASFUNC(qspr2) (char *, int *, double *,
double *, int *, double *, int *, double *);
int BLASFUNC(cspr2) (char *, int *, float *,
float *, int *, float *, int *, float *);
int BLASFUNC(zspr2) (char *, int *, double *,
double *, int *, double *, int *, double *);
int BLASFUNC(xspr2) (char *, int *, double *,
double *, int *, double *, int *, double *);
int BLASFUNC(cher) (char *, int *, float *, float *, int *,
float *, int *);
int BLASFUNC(zher) (char *, int *, double *, double *, int *,
double *, int *);
int BLASFUNC(xher) (char *, int *, double *, double *, int *,
double *, int *);
int BLASFUNC(chpr) (char *, int *, float *, float *, int *, float *);
int BLASFUNC(zhpr) (char *, int *, double *, double *, int *, double *);
int BLASFUNC(xhpr) (char *, int *, double *, double *, int *, double *);
int BLASFUNC(cher2) (char *, int *, float *,
float *, int *, float *, int *, float *, int *);
int BLASFUNC(zher2) (char *, int *, double *,
double *, int *, double *, int *, double *, int *);
int BLASFUNC(xher2) (char *, int *, double *,
double *, int *, double *, int *, double *, int *);
int BLASFUNC(chpr2) (char *, int *, float *,
float *, int *, float *, int *, float *);
int BLASFUNC(zhpr2) (char *, int *, double *,
double *, int *, double *, int *, double *);
int BLASFUNC(xhpr2) (char *, int *, double *,
double *, int *, double *, int *, double *);
int BLASFUNC(chemv) (char *, int *, float *, float *, int *,
float *, int *, float *, float *, int *);
int BLASFUNC(zhemv) (char *, int *, double *, double *, int *,
double *, int *, double *, double *, int *);
int BLASFUNC(xhemv) (char *, int *, double *, double *, int *,
double *, int *, double *, double *, int *);
int BLASFUNC(chpmv) (char *, int *, float *, float *,
float *, int *, float *, float *, int *);
int BLASFUNC(zhpmv) (char *, int *, double *, double *,
double *, int *, double *, double *, int *);
int BLASFUNC(xhpmv) (char *, int *, double *, double *,
double *, int *, double *, double *, int *);
int BLASFUNC(snorm)(char *, int *, int *, float *, int *);
int BLASFUNC(dnorm)(char *, int *, int *, double *, int *);
int BLASFUNC(cnorm)(char *, int *, int *, float *, int *);
int BLASFUNC(znorm)(char *, int *, int *, double *, int *);
int BLASFUNC(sgbmv)(char *, int *, int *, int *, int *, float *, float *, int *,
float *, int *, float *, float *, int *);
int BLASFUNC(dgbmv)(char *, int *, int *, int *, int *, double *, double *, int *,
double *, int *, double *, double *, int *);
int BLASFUNC(qgbmv)(char *, int *, int *, int *, int *, double *, double *, int *,
double *, int *, double *, double *, int *);
int BLASFUNC(cgbmv)(char *, int *, int *, int *, int *, float *, float *, int *,
float *, int *, float *, float *, int *);
int BLASFUNC(zgbmv)(char *, int *, int *, int *, int *, double *, double *, int *,
double *, int *, double *, double *, int *);
int BLASFUNC(xgbmv)(char *, int *, int *, int *, int *, double *, double *, int *,
double *, int *, double *, double *, int *);
int BLASFUNC(ssbmv)(char *, int *, int *, float *, float *, int *,
float *, int *, float *, float *, int *);
int BLASFUNC(dsbmv)(char *, int *, int *, double *, double *, int *,
double *, int *, double *, double *, int *);
int BLASFUNC(qsbmv)(char *, int *, int *, double *, double *, int *,
double *, int *, double *, double *, int *);
int BLASFUNC(csbmv)(char *, int *, int *, float *, float *, int *,
float *, int *, float *, float *, int *);
int BLASFUNC(zsbmv)(char *, int *, int *, double *, double *, int *,
double *, int *, double *, double *, int *);
int BLASFUNC(xsbmv)(char *, int *, int *, double *, double *, int *,
double *, int *, double *, double *, int *);
int BLASFUNC(chbmv)(char *, int *, int *, float *, float *, int *,
float *, int *, float *, float *, int *);
int BLASFUNC(zhbmv)(char *, int *, int *, double *, double *, int *,
double *, int *, double *, double *, int *);
int BLASFUNC(xhbmv)(char *, int *, int *, double *, double *, int *,
double *, int *, double *, double *, int *);
/* Level 3 routines */
int BLASFUNC(sgemm)(char *, char *, int *, int *, int *, float *,
float *, int *, float *, int *, float *, float *, int *);
int BLASFUNC(dgemm)(char *, char *, int *, int *, int *, double *,
double *, int *, double *, int *, double *, double *, int *);
int BLASFUNC(qgemm)(char *, char *, int *, int *, int *, double *,
double *, int *, double *, int *, double *, double *, int *);
int BLASFUNC(cgemm)(char *, char *, int *, int *, int *, float *,
float *, int *, float *, int *, float *, float *, int *);
int BLASFUNC(zgemm)(char *, char *, int *, int *, int *, double *,
double *, int *, double *, int *, double *, double *, int *);
int BLASFUNC(xgemm)(char *, char *, int *, int *, int *, double *,
double *, int *, double *, int *, double *, double *, int *);
int BLASFUNC(cgemm3m)(char *, char *, int *, int *, int *, float *,
float *, int *, float *, int *, float *, float *, int *);
int BLASFUNC(zgemm3m)(char *, char *, int *, int *, int *, double *,
double *, int *, double *, int *, double *, double *, int *);
int BLASFUNC(xgemm3m)(char *, char *, int *, int *, int *, double *,
double *, int *, double *, int *, double *, double *, int *);
int BLASFUNC(sge2mm)(char *, char *, char *, int *, int *,
float *, float *, int *, float *, int *,
float *, float *, int *);
int BLASFUNC(dge2mm)(char *, char *, char *, int *, int *,
double *, double *, int *, double *, int *,
double *, double *, int *);
int BLASFUNC(cge2mm)(char *, char *, char *, int *, int *,
float *, float *, int *, float *, int *,
float *, float *, int *);
int BLASFUNC(zge2mm)(char *, char *, char *, int *, int *,
double *, double *, int *, double *, int *,
double *, double *, int *);
int BLASFUNC(strsm)(char *, char *, char *, char *, int *, int *,
float *, float *, int *, float *, int *);
int BLASFUNC(dtrsm)(char *, char *, char *, char *, int *, int *,
double *, double *, int *, double *, int *);
int BLASFUNC(qtrsm)(char *, char *, char *, char *, int *, int *,
double *, double *, int *, double *, int *);
int BLASFUNC(ctrsm)(char *, char *, char *, char *, int *, int *,
float *, float *, int *, float *, int *);
int BLASFUNC(ztrsm)(char *, char *, char *, char *, int *, int *,
double *, double *, int *, double *, int *);
int BLASFUNC(xtrsm)(char *, char *, char *, char *, int *, int *,
double *, double *, int *, double *, int *);
int BLASFUNC(strmm)(char *, char *, char *, char *, int *, int *,
float *, float *, int *, float *, int *);
int BLASFUNC(dtrmm)(char *, char *, char *, char *, int *, int *,
double *, double *, int *, double *, int *);
int BLASFUNC(qtrmm)(char *, char *, char *, char *, int *, int *,
double *, double *, int *, double *, int *);
int BLASFUNC(ctrmm)(char *, char *, char *, char *, int *, int *,
float *, float *, int *, float *, int *);
int BLASFUNC(ztrmm)(char *, char *, char *, char *, int *, int *,
double *, double *, int *, double *, int *);
int BLASFUNC(xtrmm)(char *, char *, char *, char *, int *, int *,
double *, double *, int *, double *, int *);
int BLASFUNC(ssymm)(char *, char *, int *, int *, float *, float *, int *,
float *, int *, float *, float *, int *);
int BLASFUNC(dsymm)(char *, char *, int *, int *, double *, double *, int *,
double *, int *, double *, double *, int *);
int BLASFUNC(qsymm)(char *, char *, int *, int *, double *, double *, int *,
double *, int *, double *, double *, int *);
int BLASFUNC(csymm)(char *, char *, int *, int *, float *, float *, int *,
float *, int *, float *, float *, int *);
int BLASFUNC(zsymm)(char *, char *, int *, int *, double *, double *, int *,
double *, int *, double *, double *, int *);
int BLASFUNC(xsymm)(char *, char *, int *, int *, double *, double *, int *,
double *, int *, double *, double *, int *);
int BLASFUNC(csymm3m)(char *, char *, int *, int *, float *, float *, int *,
float *, int *, float *, float *, int *);
int BLASFUNC(zsymm3m)(char *, char *, int *, int *, double *, double *, int *,
double *, int *, double *, double *, int *);
int BLASFUNC(xsymm3m)(char *, char *, int *, int *, double *, double *, int *,
double *, int *, double *, double *, int *);
int BLASFUNC(ssyrk)(char *, char *, int *, int *, float *, float *, int *,
float *, float *, int *);
int BLASFUNC(dsyrk)(char *, char *, int *, int *, double *, double *, int *,
double *, double *, int *);
int BLASFUNC(qsyrk)(char *, char *, int *, int *, double *, double *, int *,
double *, double *, int *);
int BLASFUNC(csyrk)(char *, char *, int *, int *, float *, float *, int *,
float *, float *, int *);
int BLASFUNC(zsyrk)(char *, char *, int *, int *, double *, double *, int *,
double *, double *, int *);
int BLASFUNC(xsyrk)(char *, char *, int *, int *, double *, double *, int *,
double *, double *, int *);
int BLASFUNC(ssyr2k)(char *, char *, int *, int *, float *, float *, int *,
float *, int *, float *, float *, int *);
int BLASFUNC(dsyr2k)(char *, char *, int *, int *, double *, double *, int *,
double*, int *, double *, double *, int *);
int BLASFUNC(qsyr2k)(char *, char *, int *, int *, double *, double *, int *,
double*, int *, double *, double *, int *);
int BLASFUNC(csyr2k)(char *, char *, int *, int *, float *, float *, int *,
float *, int *, float *, float *, int *);
int BLASFUNC(zsyr2k)(char *, char *, int *, int *, double *, double *, int *,
double*, int *, double *, double *, int *);
int BLASFUNC(xsyr2k)(char *, char *, int *, int *, double *, double *, int *,
double*, int *, double *, double *, int *);
int BLASFUNC(chemm)(char *, char *, int *, int *, float *, float *, int *,
float *, int *, float *, float *, int *);
int BLASFUNC(zhemm)(char *, char *, int *, int *, double *, double *, int *,
double *, int *, double *, double *, int *);
int BLASFUNC(xhemm)(char *, char *, int *, int *, double *, double *, int *,
double *, int *, double *, double *, int *);
int BLASFUNC(chemm3m)(char *, char *, int *, int *, float *, float *, int *,
float *, int *, float *, float *, int *);
int BLASFUNC(zhemm3m)(char *, char *, int *, int *, double *, double *, int *,
double *, int *, double *, double *, int *);
int BLASFUNC(xhemm3m)(char *, char *, int *, int *, double *, double *, int *,
double *, int *, double *, double *, int *);
int BLASFUNC(cherk)(char *, char *, int *, int *, float *, float *, int *,
float *, float *, int *);
int BLASFUNC(zherk)(char *, char *, int *, int *, double *, double *, int *,
double *, double *, int *);
int BLASFUNC(xherk)(char *, char *, int *, int *, double *, double *, int *,
double *, double *, int *);
int BLASFUNC(cher2k)(char *, char *, int *, int *, float *, float *, int *,
float *, int *, float *, float *, int *);
int BLASFUNC(zher2k)(char *, char *, int *, int *, double *, double *, int *,
double*, int *, double *, double *, int *);
int BLASFUNC(xher2k)(char *, char *, int *, int *, double *, double *, int *,
double*, int *, double *, double *, int *);
int BLASFUNC(cher2m)(char *, char *, char *, int *, int *, float *, float *, int *,
float *, int *, float *, float *, int *);
int BLASFUNC(zher2m)(char *, char *, char *, int *, int *, double *, double *, int *,
double*, int *, double *, double *, int *);
int BLASFUNC(xher2m)(char *, char *, char *, int *, int *, double *, double *, int *,
double*, int *, double *, double *, int *);
int BLASFUNC(sgemt)(char *, int *, int *, float *, float *, int *,
float *, int *);
int BLASFUNC(dgemt)(char *, int *, int *, double *, double *, int *,
double *, int *);
int BLASFUNC(cgemt)(char *, int *, int *, float *, float *, int *,
float *, int *);
int BLASFUNC(zgemt)(char *, int *, int *, double *, double *, int *,
double *, int *);
int BLASFUNC(sgema)(char *, char *, int *, int *, float *,
float *, int *, float *, float *, int *, float *, int *);
int BLASFUNC(dgema)(char *, char *, int *, int *, double *,
double *, int *, double*, double *, int *, double*, int *);
int BLASFUNC(cgema)(char *, char *, int *, int *, float *,
float *, int *, float *, float *, int *, float *, int *);
int BLASFUNC(zgema)(char *, char *, int *, int *, double *,
double *, int *, double*, double *, int *, double*, int *);
int BLASFUNC(sgems)(char *, char *, int *, int *, float *,
float *, int *, float *, float *, int *, float *, int *);
int BLASFUNC(dgems)(char *, char *, int *, int *, double *,
double *, int *, double*, double *, int *, double*, int *);
int BLASFUNC(cgems)(char *, char *, int *, int *, float *,
float *, int *, float *, float *, int *, float *, int *);
int BLASFUNC(zgems)(char *, char *, int *, int *, double *,
double *, int *, double*, double *, int *, double*, int *);
int BLASFUNC(sgetf2)(int *, int *, float *, int *, int *, int *);
int BLASFUNC(dgetf2)(int *, int *, double *, int *, int *, int *);
int BLASFUNC(qgetf2)(int *, int *, double *, int *, int *, int *);
int BLASFUNC(cgetf2)(int *, int *, float *, int *, int *, int *);
int BLASFUNC(zgetf2)(int *, int *, double *, int *, int *, int *);
int BLASFUNC(xgetf2)(int *, int *, double *, int *, int *, int *);
int BLASFUNC(sgetrf)(int *, int *, float *, int *, int *, int *);
int BLASFUNC(dgetrf)(int *, int *, double *, int *, int *, int *);
int BLASFUNC(qgetrf)(int *, int *, double *, int *, int *, int *);
int BLASFUNC(cgetrf)(int *, int *, float *, int *, int *, int *);
int BLASFUNC(zgetrf)(int *, int *, double *, int *, int *, int *);
int BLASFUNC(xgetrf)(int *, int *, double *, int *, int *, int *);
int BLASFUNC(slaswp)(int *, float *, int *, int *, int *, int *, int *);
int BLASFUNC(dlaswp)(int *, double *, int *, int *, int *, int *, int *);
int BLASFUNC(qlaswp)(int *, double *, int *, int *, int *, int *, int *);
int BLASFUNC(claswp)(int *, float *, int *, int *, int *, int *, int *);
int BLASFUNC(zlaswp)(int *, double *, int *, int *, int *, int *, int *);
int BLASFUNC(xlaswp)(int *, double *, int *, int *, int *, int *, int *);
int BLASFUNC(sgetrs)(char *, int *, int *, float *, int *, int *, float *, int *, int *);
int BLASFUNC(dgetrs)(char *, int *, int *, double *, int *, int *, double *, int *, int *);
int BLASFUNC(qgetrs)(char *, int *, int *, double *, int *, int *, double *, int *, int *);
int BLASFUNC(cgetrs)(char *, int *, int *, float *, int *, int *, float *, int *, int *);
int BLASFUNC(zgetrs)(char *, int *, int *, double *, int *, int *, double *, int *, int *);
int BLASFUNC(xgetrs)(char *, int *, int *, double *, int *, int *, double *, int *, int *);
int BLASFUNC(sgesv)(int *, int *, float *, int *, int *, float *, int *, int *);
int BLASFUNC(dgesv)(int *, int *, double *, int *, int *, double*, int *, int *);
int BLASFUNC(qgesv)(int *, int *, double *, int *, int *, double*, int *, int *);
int BLASFUNC(cgesv)(int *, int *, float *, int *, int *, float *, int *, int *);
int BLASFUNC(zgesv)(int *, int *, double *, int *, int *, double*, int *, int *);
int BLASFUNC(xgesv)(int *, int *, double *, int *, int *, double*, int *, int *);
int BLASFUNC(spotf2)(char *, int *, float *, int *, int *);
int BLASFUNC(dpotf2)(char *, int *, double *, int *, int *);
int BLASFUNC(qpotf2)(char *, int *, double *, int *, int *);
int BLASFUNC(cpotf2)(char *, int *, float *, int *, int *);
int BLASFUNC(zpotf2)(char *, int *, double *, int *, int *);
int BLASFUNC(xpotf2)(char *, int *, double *, int *, int *);
int BLASFUNC(spotrf)(char *, int *, float *, int *, int *);
int BLASFUNC(dpotrf)(char *, int *, double *, int *, int *);
int BLASFUNC(qpotrf)(char *, int *, double *, int *, int *);
int BLASFUNC(cpotrf)(char *, int *, float *, int *, int *);
int BLASFUNC(zpotrf)(char *, int *, double *, int *, int *);
int BLASFUNC(xpotrf)(char *, int *, double *, int *, int *);
int BLASFUNC(slauu2)(char *, int *, float *, int *, int *);
int BLASFUNC(dlauu2)(char *, int *, double *, int *, int *);
int BLASFUNC(qlauu2)(char *, int *, double *, int *, int *);
int BLASFUNC(clauu2)(char *, int *, float *, int *, int *);
int BLASFUNC(zlauu2)(char *, int *, double *, int *, int *);
int BLASFUNC(xlauu2)(char *, int *, double *, int *, int *);
int BLASFUNC(slauum)(char *, int *, float *, int *, int *);
int BLASFUNC(dlauum)(char *, int *, double *, int *, int *);
int BLASFUNC(qlauum)(char *, int *, double *, int *, int *);
int BLASFUNC(clauum)(char *, int *, float *, int *, int *);
int BLASFUNC(zlauum)(char *, int *, double *, int *, int *);
int BLASFUNC(xlauum)(char *, int *, double *, int *, int *);
int BLASFUNC(strti2)(char *, char *, int *, float *, int *, int *);
int BLASFUNC(dtrti2)(char *, char *, int *, double *, int *, int *);
int BLASFUNC(qtrti2)(char *, char *, int *, double *, int *, int *);
int BLASFUNC(ctrti2)(char *, char *, int *, float *, int *, int *);
int BLASFUNC(ztrti2)(char *, char *, int *, double *, int *, int *);
int BLASFUNC(xtrti2)(char *, char *, int *, double *, int *, int *);
int BLASFUNC(strtri)(char *, char *, int *, float *, int *, int *);
int BLASFUNC(dtrtri)(char *, char *, int *, double *, int *, int *);
int BLASFUNC(qtrtri)(char *, char *, int *, double *, int *, int *);
int BLASFUNC(ctrtri)(char *, char *, int *, float *, int *, int *);
int BLASFUNC(ztrtri)(char *, char *, int *, double *, int *, int *);
int BLASFUNC(xtrtri)(char *, char *, int *, double *, int *, int *);
int BLASFUNC(spotri)(char *, int *, float *, int *, int *);
int BLASFUNC(dpotri)(char *, int *, double *, int *, int *);
int BLASFUNC(qpotri)(char *, int *, double *, int *, int *);
int BLASFUNC(cpotri)(char *, int *, float *, int *, int *);
int BLASFUNC(zpotri)(char *, int *, double *, int *, int *);
int BLASFUNC(xpotri)(char *, int *, double *, int *, int *);
#endif
| Unknown |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/BLAS/c_interface_base.h | .h | 1,634 | 74 |
#ifndef BTL_C_INTERFACE_BASE_H
#define BTL_C_INTERFACE_BASE_H
#include "utilities.h"
#include <vector>
template<class real> class c_interface_base
{
public:
typedef real real_type;
typedef std::vector<real> stl_vector;
typedef std::vector<stl_vector > stl_matrix;
typedef real* gene_matrix;
typedef real* gene_vector;
static void free_matrix(gene_matrix & A, int /*N*/){
delete[] A;
}
static void free_vector(gene_vector & B){
delete[] B;
}
static inline void matrix_from_stl(gene_matrix & A, stl_matrix & A_stl){
int N = A_stl.size();
A = new real[N*N];
for (int j=0;j<N;j++)
for (int i=0;i<N;i++)
A[i+N*j] = A_stl[j][i];
}
static inline void vector_from_stl(gene_vector & B, stl_vector & B_stl){
int N = B_stl.size();
B = new real[N];
for (int i=0;i<N;i++)
B[i] = B_stl[i];
}
static inline void vector_to_stl(gene_vector & B, stl_vector & B_stl){
int N = B_stl.size();
for (int i=0;i<N;i++)
B_stl[i] = B[i];
}
static inline void matrix_to_stl(gene_matrix & A, stl_matrix & A_stl){
int N = A_stl.size();
for (int j=0;j<N;j++){
A_stl[j].resize(N);
for (int i=0;i<N;i++)
A_stl[j][i] = A[i+N*j];
}
}
static inline void copy_vector(const gene_vector & source, gene_vector & cible, int N){
for (int i=0;i<N;i++)
cible[i]=source[i];
}
static inline void copy_matrix(const gene_matrix & source, gene_matrix & cible, int N){
for (int j=0;j<N;j++){
for (int i=0;i<N;i++){
cible[i+N*j] = source[i+N*j];
}
}
}
};
#endif
| Unknown |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/BLAS/main.cpp | .cpp | 2,963 | 74 | //=====================================================
// File : main.cpp
// Author : L. Plagne <laurent.plagne@edf.fr)>
// Copyright (C) EDF R&D, lun sep 30 14:23:28 CEST 2002
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#include "utilities.h"
#include "blas_interface.hh"
#include "bench.hh"
#include "basic_actions.hh"
#include "action_cholesky.hh"
#include "action_lu_decomp.hh"
#include "action_partial_lu.hh"
#include "action_trisolve_matrix.hh"
#ifdef HAS_LAPACK
#include "action_hessenberg.hh"
#endif
BTL_MAIN;
int main()
{
bench<Action_axpy<blas_interface<REAL_TYPE> > >(MIN_AXPY,MAX_AXPY,NB_POINT);
bench<Action_axpby<blas_interface<REAL_TYPE> > >(MIN_AXPY,MAX_AXPY,NB_POINT);
bench<Action_matrix_vector_product<blas_interface<REAL_TYPE> > >(MIN_MV,MAX_MV,NB_POINT);
bench<Action_atv_product<blas_interface<REAL_TYPE> > >(MIN_MV,MAX_MV,NB_POINT);
bench<Action_symv<blas_interface<REAL_TYPE> > >(MIN_MV,MAX_MV,NB_POINT);
bench<Action_syr2<blas_interface<REAL_TYPE> > >(MIN_MV,MAX_MV,NB_POINT);
bench<Action_ger<blas_interface<REAL_TYPE> > >(MIN_MV,MAX_MV,NB_POINT);
bench<Action_rot<blas_interface<REAL_TYPE> > >(MIN_AXPY,MAX_AXPY,NB_POINT);
bench<Action_matrix_matrix_product<blas_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
// bench<Action_ata_product<blas_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
bench<Action_aat_product<blas_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
bench<Action_trisolve<blas_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
bench<Action_trisolve_matrix<blas_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
bench<Action_trmm<blas_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
bench<Action_cholesky<blas_interface<REAL_TYPE> > >(MIN_LU,MAX_LU,NB_POINT);
bench<Action_partial_lu<blas_interface<REAL_TYPE> > >(MIN_LU,MAX_LU,NB_POINT);
#ifdef HAS_LAPACK
// bench<Action_lu_decomp<blas_interface<REAL_TYPE> > >(MIN_LU,MAX_LU,NB_POINT);
bench<Action_hessenberg<blas_interface<REAL_TYPE> > >(MIN_LU,MAX_LU,NB_POINT);
bench<Action_tridiagonalization<blas_interface<REAL_TYPE> > >(MIN_LU,MAX_LU,NB_POINT);
#endif
//bench<Action_lu_solve<blas_LU_solve_interface<REAL_TYPE> > >(MIN_LU,MAX_LU,NB_POINT);
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/BLAS/blas_interface.hh | .hh | 2,891 | 84 | //=====================================================
// File : blas_interface.hh
// Author : L. Plagne <laurent.plagne@edf.fr)>
// Copyright (C) EDF R&D, lun sep 30 14:23:28 CEST 2002
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#ifndef blas_PRODUIT_MATRICE_VECTEUR_HH
#define blas_PRODUIT_MATRICE_VECTEUR_HH
#include <c_interface_base.h>
#include <complex>
extern "C"
{
#include "blas.h"
// Cholesky Factorization
// void spotrf_(const char* uplo, const int* n, float *a, const int* ld, int* info);
// void dpotrf_(const char* uplo, const int* n, double *a, const int* ld, int* info);
void ssytrd_(char *uplo, const int *n, float *a, const int *lda, float *d, float *e, float *tau, float *work, int *lwork, int *info );
void dsytrd_(char *uplo, const int *n, double *a, const int *lda, double *d, double *e, double *tau, double *work, int *lwork, int *info );
void sgehrd_( const int *n, int *ilo, int *ihi, float *a, const int *lda, float *tau, float *work, int *lwork, int *info );
void dgehrd_( const int *n, int *ilo, int *ihi, double *a, const int *lda, double *tau, double *work, int *lwork, int *info );
// LU row pivoting
// void dgetrf_( int *m, int *n, double *a, int *lda, int *ipiv, int *info );
// void sgetrf_(const int* m, const int* n, float *a, const int* ld, int* ipivot, int* info);
// LU full pivoting
void sgetc2_(const int* n, float *a, const int *lda, int *ipiv, int *jpiv, int*info );
void dgetc2_(const int* n, double *a, const int *lda, int *ipiv, int *jpiv, int*info );
#ifdef HAS_LAPACK
#endif
}
#define MAKE_STRING2(S) #S
#define MAKE_STRING(S) MAKE_STRING2(S)
#define CAT2(A,B) A##B
#define CAT(A,B) CAT2(A,B)
template<class real> class blas_interface;
static char notrans = 'N';
static char trans = 'T';
static char nonunit = 'N';
static char lower = 'L';
static char right = 'R';
static char left = 'L';
static int intone = 1;
#define SCALAR float
#define SCALAR_PREFIX s
#include "blas_interface_impl.hh"
#undef SCALAR
#undef SCALAR_PREFIX
#define SCALAR double
#define SCALAR_PREFIX d
#include "blas_interface_impl.hh"
#undef SCALAR
#undef SCALAR_PREFIX
#endif
| Unknown |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/mtl4/main.cpp | .cpp | 1,943 | 47 | //=====================================================
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#include "utilities.h"
#include "mtl4_interface.hh"
#include "bench.hh"
#include "basic_actions.hh"
#include "action_cholesky.hh"
// #include "action_lu_decomp.hh"
BTL_MAIN;
int main()
{
bench<Action_axpy<mtl4_interface<REAL_TYPE> > >(MIN_AXPY,MAX_AXPY,NB_POINT);
bench<Action_axpby<mtl4_interface<REAL_TYPE> > >(MIN_AXPY,MAX_AXPY,NB_POINT);
bench<Action_matrix_vector_product<mtl4_interface<REAL_TYPE> > >(MIN_MV,MAX_MV,NB_POINT);
bench<Action_atv_product<mtl4_interface<REAL_TYPE> > >(MIN_MV,MAX_MV,NB_POINT);
bench<Action_matrix_matrix_product<mtl4_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
// bench<Action_ata_product<mtl4_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
// bench<Action_aat_product<mtl4_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
bench<Action_trisolve<mtl4_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
// bench<Action_cholesky<mtl4_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
// bench<Action_lu_decomp<mtl4_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/mtl4/mtl4_LU_solve_interface.hh | .hh | 5,364 | 193 | //=====================================================
// File : blitz_LU_solve_interface.hh
// Author : L. Plagne <laurent.plagne@edf.fr)>
// Copyright (C) EDF R&D, lun sep 30 14:23:31 CEST 2002
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#ifndef BLITZ_LU_SOLVE_INTERFACE_HH
#define BLITZ_LU_SOLVE_INTERFACE_HH
#include "blitz/array.h"
#include <vector>
BZ_USING_NAMESPACE(blitz)
template<class real>
class blitz_LU_solve_interface : public blitz_interface<real>
{
public :
typedef typename blitz_interface<real>::gene_matrix gene_matrix;
typedef typename blitz_interface<real>::gene_vector gene_vector;
typedef blitz::Array<int,1> Pivot_Vector;
inline static void new_Pivot_Vector(Pivot_Vector & pivot,int N)
{
pivot.resize(N);
}
inline static void free_Pivot_Vector(Pivot_Vector & pivot)
{
return;
}
static inline real matrix_vector_product_sliced(const gene_matrix & A, gene_vector B, int row, int col_start, int col_end)
{
real somme=0.;
for (int j=col_start ; j<col_end+1 ; j++){
somme+=A(row,j)*B(j);
}
return somme;
}
static inline real matrix_matrix_product_sliced(gene_matrix & A, int row, int col_start, int col_end, gene_matrix & B, int row_shift, int col )
{
real somme=0.;
for (int j=col_start ; j<col_end+1 ; j++){
somme+=A(row,j)*B(j+row_shift,col);
}
return somme;
}
inline static void LU_factor(gene_matrix & LU, Pivot_Vector & pivot, int N)
{
ASSERT( LU.rows()==LU.cols() ) ;
int index_max = 0 ;
real big = 0. ;
real theSum = 0. ;
real dum = 0. ;
// Get the implicit scaling information :
gene_vector ImplicitScaling( N ) ;
for( int i=0; i<N; i++ ) {
big = 0. ;
for( int j=0; j<N; j++ ) {
if( abs( LU( i, j ) )>=big ) big = abs( LU( i, j ) ) ;
}
if( big==0. ) {
INFOS( "blitz_LU_factor::Singular matrix" ) ;
exit( 0 ) ;
}
ImplicitScaling( i ) = 1./big ;
}
// Loop over columns of Crout's method :
for( int j=0; j<N; j++ ) {
for( int i=0; i<j; i++ ) {
theSum = LU( i, j ) ;
theSum -= matrix_matrix_product_sliced(LU, i, 0, i-1, LU, 0, j) ;
// theSum -= sum( LU( i, Range( fromStart, i-1 ) )*LU( Range( fromStart, i-1 ), j ) ) ;
LU( i, j ) = theSum ;
}
// Search for the largest pivot element :
big = 0. ;
for( int i=j; i<N; i++ ) {
theSum = LU( i, j ) ;
theSum -= matrix_matrix_product_sliced(LU, i, 0, j-1, LU, 0, j) ;
// theSum -= sum( LU( i, Range( fromStart, j-1 ) )*LU( Range( fromStart, j-1 ), j ) ) ;
LU( i, j ) = theSum ;
if( (ImplicitScaling( i )*abs( theSum ))>=big ) {
dum = ImplicitScaling( i )*abs( theSum ) ;
big = dum ;
index_max = i ;
}
}
// Interchanging rows and the scale factor :
if( j!=index_max ) {
for( int k=0; k<N; k++ ) {
dum = LU( index_max, k ) ;
LU( index_max, k ) = LU( j, k ) ;
LU( j, k ) = dum ;
}
ImplicitScaling( index_max ) = ImplicitScaling( j ) ;
}
pivot( j ) = index_max ;
if ( LU( j, j )==0. ) LU( j, j ) = 1.e-20 ;
// Divide by the pivot element :
if( j<N ) {
dum = 1./LU( j, j ) ;
for( int i=j+1; i<N; i++ ) LU( i, j ) *= dum ;
}
}
}
inline static void LU_solve(const gene_matrix & LU, const Pivot_Vector pivot, gene_vector &B, gene_vector X, int N)
{
// Pour conserver le meme header, on travaille sur X, copie du second-membre B
X = B.copy() ;
ASSERT( LU.rows()==LU.cols() ) ;
firstIndex indI ;
// Forward substitution :
int ii = 0 ;
real theSum = 0. ;
for( int i=0; i<N; i++ ) {
int ip = pivot( i ) ;
theSum = X( ip ) ;
// theSum = B( ip ) ;
X( ip ) = X( i ) ;
// B( ip ) = B( i ) ;
if( ii ) {
theSum -= matrix_vector_product_sliced(LU, X, i, ii-1, i-1) ;
// theSum -= sum( LU( i, Range( ii-1, i-1 ) )*X( Range( ii-1, i-1 ) ) ) ;
// theSum -= sum( LU( i, Range( ii-1, i-1 ) )*B( Range( ii-1, i-1 ) ) ) ;
} else if( theSum ) {
ii = i+1 ;
}
X( i ) = theSum ;
// B( i ) = theSum ;
}
// Backsubstitution :
for( int i=N-1; i>=0; i-- ) {
theSum = X( i ) ;
// theSum = B( i ) ;
theSum -= matrix_vector_product_sliced(LU, X, i, i+1, N) ;
// theSum -= sum( LU( i, Range( i+1, toEnd ) )*X( Range( i+1, toEnd ) ) ) ;
// theSum -= sum( LU( i, Range( i+1, toEnd ) )*B( Range( i+1, toEnd ) ) ) ;
// Store a component of the solution vector :
X( i ) = theSum/LU( i, i ) ;
// B( i ) = theSum/LU( i, i ) ;
}
}
};
#endif
| Unknown |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/mtl4/mtl4_interface.hh | .hh | 4,210 | 145 | //=====================================================
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#ifndef MTL4_INTERFACE_HH
#define MTL4_INTERFACE_HH
#include <boost/numeric/mtl/mtl.hpp>
#include <boost/numeric/mtl/utility/range_generator.hpp>
// #include <boost/numeric/mtl/operation/cholesky.hpp>
#include <vector>
using namespace mtl;
template<class real>
class mtl4_interface {
public :
typedef real real_type ;
typedef std::vector<real> stl_vector;
typedef std::vector<stl_vector > stl_matrix;
typedef mtl::dense2D<real, mtl::matrix::parameters<mtl::tag::col_major> > gene_matrix;
typedef mtl::dense_vector<real> gene_vector;
static inline std::string name() { return "mtl4"; }
static void free_matrix(gene_matrix & A, int N){
return ;
}
static void free_vector(gene_vector & B){
return ;
}
static inline void matrix_from_stl(gene_matrix & A, stl_matrix & A_stl){
A.change_dim(A_stl[0].size(), A_stl.size());
for (int j=0; j<A_stl.size() ; j++){
for (int i=0; i<A_stl[j].size() ; i++){
A(i,j) = A_stl[j][i];
}
}
}
static inline void vector_from_stl(gene_vector & B, stl_vector & B_stl){
B.change_dim(B_stl.size());
for (int i=0; i<B_stl.size() ; i++){
B[i] = B_stl[i];
}
}
static inline void vector_to_stl(gene_vector & B, stl_vector & B_stl){
for (int i=0; i<B_stl.size() ; i++){
B_stl[i] = B[i];
}
}
static inline void matrix_to_stl(gene_matrix & A, stl_matrix & A_stl){
int N=A_stl.size();
for (int j=0;j<N;j++){
A_stl[j].resize(N);
for (int i=0;i<N;i++){
A_stl[j][i] = A(i,j);
}
}
}
static inline void matrix_matrix_product(const gene_matrix & A, const gene_matrix & B, gene_matrix & X, int N){
X = (A*B);
// morton_dense<double, doppled_64_row_mask> C(N,N);
// C = B;
// X = (A*C);
}
static inline void transposed_matrix_matrix_product(const gene_matrix & A, const gene_matrix & B, gene_matrix & X, int N){
X = (trans(A)*trans(B));
}
// static inline void ata_product(const gene_matrix & A, gene_matrix & X, int N){
// X = (trans(A)*A);
// }
static inline void aat_product(const gene_matrix & A, gene_matrix & X, int N){
X = (A*trans(A));
}
static inline void matrix_vector_product(gene_matrix & A, gene_vector & B, gene_vector & X, int N){
X = (A*B);
}
static inline void atv_product(gene_matrix & A, gene_vector & B, gene_vector & X, int N){
X = (trans(A)*B);
}
static inline void axpy(const real coef, const gene_vector & X, gene_vector & Y, int N){
Y += coef * X;
}
static inline void axpby(real a, const gene_vector & X, real b, gene_vector & Y, int N){
Y = a*X + b*Y;
}
// static inline void cholesky(const gene_matrix & X, gene_matrix & C, int N){
// C = X;
// recursive_cholesky(C);
// }
// static inline void lu_decomp(const gene_matrix & X, gene_matrix & R, int N){
// R = X;
// std::vector<int> ipvt(N);
// lu_factor(R, ipvt);
// }
static inline void trisolve_lower(const gene_matrix & L, const gene_vector& B, gene_vector & X, int N){
X = lower_trisolve(L, B);
}
static inline void copy_matrix(const gene_matrix & source, gene_matrix & cible, int N){
cible = source;
}
static inline void copy_vector(const gene_vector & source, gene_vector & cible, int N){
cible = source;
}
};
#endif
| Unknown |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/STL/STL_interface.hh | .hh | 5,838 | 245 | //=====================================================
// File : STL_interface.hh
// Author : L. Plagne <laurent.plagne@edf.fr)>
// Copyright (C) EDF R&D, lun sep 30 14:23:24 CEST 2002
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#ifndef STL_INTERFACE_HH
#define STL_INTERFACE_HH
#include <string>
#include <vector>
#include "utilities.h"
using namespace std;
template<class real>
class STL_interface{
public :
typedef real real_type ;
typedef std::vector<real> stl_vector;
typedef std::vector<stl_vector > stl_matrix;
typedef stl_matrix gene_matrix;
typedef stl_vector gene_vector;
static inline std::string name( void )
{
return "STL";
}
static void free_matrix(gene_matrix & /*A*/, int /*N*/){}
static void free_vector(gene_vector & /*B*/){}
static inline void matrix_from_stl(gene_matrix & A, stl_matrix & A_stl){
A = A_stl;
}
static inline void vector_from_stl(gene_vector & B, stl_vector & B_stl){
B = B_stl;
}
static inline void vector_to_stl(gene_vector & B, stl_vector & B_stl){
B_stl = B ;
}
static inline void matrix_to_stl(gene_matrix & A, stl_matrix & A_stl){
A_stl = A ;
}
static inline void copy_vector(const gene_vector & source, gene_vector & cible, int N){
for (int i=0;i<N;i++){
cible[i]=source[i];
}
}
static inline void copy_matrix(const gene_matrix & source, gene_matrix & cible, int N){
for (int i=0;i<N;i++)
for (int j=0;j<N;j++)
cible[i][j]=source[i][j];
}
// static inline void ata_product(const gene_matrix & A, gene_matrix & X, int N)
// {
// real somme;
// for (int j=0;j<N;j++){
// for (int i=0;i<N;i++){
// somme=0.0;
// for (int k=0;k<N;k++)
// somme += A[i][k]*A[j][k];
// X[j][i]=somme;
// }
// }
// }
static inline void aat_product(const gene_matrix & A, gene_matrix & X, int N)
{
real somme;
for (int j=0;j<N;j++){
for (int i=0;i<N;i++){
somme=0.0;
if(i>=j)
{
for (int k=0;k<N;k++){
somme+=A[k][i]*A[k][j];
}
X[j][i]=somme;
}
}
}
}
static inline void matrix_matrix_product(const gene_matrix & A, const gene_matrix & B, gene_matrix & X, int N)
{
real somme;
for (int j=0;j<N;j++){
for (int i=0;i<N;i++){
somme=0.0;
for (int k=0;k<N;k++)
somme+=A[k][i]*B[j][k];
X[j][i]=somme;
}
}
}
static inline void matrix_vector_product(gene_matrix & A, gene_vector & B, gene_vector & X, int N)
{
real somme;
for (int i=0;i<N;i++){
somme=0.0;
for (int j=0;j<N;j++)
somme+=A[j][i]*B[j];
X[i]=somme;
}
}
static inline void symv(gene_matrix & A, gene_vector & B, gene_vector & X, int N)
{
for (int j=0; j<N; ++j)
X[j] = 0;
for (int j=0; j<N; ++j)
{
real t1 = B[j];
real t2 = 0;
X[j] += t1 * A[j][j];
for (int i=j+1; i<N; ++i) {
X[i] += t1 * A[j][i];
t2 += A[j][i] * B[i];
}
X[j] += t2;
}
}
static inline void syr2(gene_matrix & A, gene_vector & B, gene_vector & X, int N)
{
for (int j=0; j<N; ++j)
{
for (int i=j; i<N; ++i)
A[j][i] += B[i]*X[j] + B[j]*X[i];
}
}
static inline void ger(gene_matrix & A, gene_vector & X, gene_vector & Y, int N)
{
for (int j=0; j<N; ++j)
{
for (int i=j; i<N; ++i)
A[j][i] += X[i]*Y[j];
}
}
static inline void atv_product(gene_matrix & A, gene_vector & B, gene_vector & X, int N)
{
real somme;
for (int i=0;i<N;i++){
somme = 0.0;
for (int j=0;j<N;j++)
somme += A[i][j]*B[j];
X[i] = somme;
}
}
static inline void axpy(real coef, const gene_vector & X, gene_vector & Y, int N){
for (int i=0;i<N;i++)
Y[i]+=coef*X[i];
}
static inline void axpby(real a, const gene_vector & X, real b, gene_vector & Y, int N){
for (int i=0;i<N;i++)
Y[i] = a*X[i] + b*Y[i];
}
static inline void trisolve_lower(const gene_matrix & L, const gene_vector & B, gene_vector & X, int N){
copy_vector(B,X,N);
for(int i=0; i<N; ++i)
{
X[i] /= L[i][i];
real tmp = X[i];
for (int j=i+1; j<N; ++j)
X[j] -= tmp * L[i][j];
}
}
static inline real norm_diff(const stl_vector & A, const stl_vector & B)
{
int N=A.size();
real somme=0.0;
real somme2=0.0;
for (int i=0;i<N;i++){
real diff=A[i]-B[i];
somme+=diff*diff;
somme2+=A[i]*A[i];
}
return somme/somme2;
}
static inline real norm_diff(const stl_matrix & A, const stl_matrix & B)
{
int N=A[0].size();
real somme=0.0;
real somme2=0.0;
for (int i=0;i<N;i++){
for (int j=0;j<N;j++){
real diff=A[i][j] - B[i][j];
somme += diff*diff;
somme2 += A[i][j]*A[i][j];
}
}
return somme/somme2;
}
static inline void display_vector(const stl_vector & A)
{
int N=A.size();
for (int i=0;i<N;i++){
INFOS("A["<<i<<"]="<<A[i]<<endl);
}
}
};
#endif
| Unknown |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/STL/main.cpp | .cpp | 1,828 | 43 | //=====================================================
// File : main.cpp
// Author : L. Plagne <laurent.plagne@edf.fr)>
// Copyright (C) EDF R&D, lun sep 30 14:23:23 CEST 2002
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#include "utilities.h"
#include "STL_interface.hh"
#include "bench.hh"
#include "basic_actions.hh"
BTL_MAIN;
int main()
{
bench<Action_axpy<STL_interface<REAL_TYPE> > >(MIN_AXPY,MAX_AXPY,NB_POINT);
bench<Action_axpby<STL_interface<REAL_TYPE> > >(MIN_AXPY,MAX_AXPY,NB_POINT);
bench<Action_matrix_vector_product<STL_interface<REAL_TYPE> > >(MIN_MV,MAX_MV,NB_POINT);
bench<Action_atv_product<STL_interface<REAL_TYPE> > >(MIN_MV,MAX_MV,NB_POINT);
bench<Action_symv<STL_interface<REAL_TYPE> > >(MIN_MV,MAX_MV,NB_POINT);
bench<Action_syr2<STL_interface<REAL_TYPE> > >(MIN_MV,MAX_MV,NB_POINT);
bench<Action_matrix_matrix_product<STL_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
bench<Action_ata_product<STL_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
bench<Action_aat_product<STL_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/eigen3/main_vecmat.cpp | .cpp | 1,447 | 37 | //=====================================================
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#include "utilities.h"
#include "eigen3_interface.hh"
#include "bench.hh"
#include "basic_actions.hh"
BTL_MAIN;
int main()
{
bench<Action_matrix_vector_product<eigen3_interface<REAL_TYPE> > >(MIN_MV,MAX_MV,NB_POINT);
bench<Action_atv_product<eigen3_interface<REAL_TYPE> > >(MIN_MV,MAX_MV,NB_POINT);
bench<Action_symv<eigen3_interface<REAL_TYPE> > >(MIN_MV,MAX_MV,NB_POINT);
bench<Action_syr2<eigen3_interface<REAL_TYPE> > >(MIN_MV,MAX_MV,NB_POINT);
bench<Action_ger<eigen3_interface<REAL_TYPE> > >(MIN_MV,MAX_MV,NB_POINT);
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/eigen3/btl_tiny_eigen3.cpp | .cpp | 1,664 | 47 | //=====================================================
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#include "utilities.h"
#include "eigen3_interface.hh"
#include "static/bench_static.hh"
#include "action_matrix_vector_product.hh"
#include "action_matrix_matrix_product.hh"
#include "action_axpy.hh"
#include "action_lu_solve.hh"
#include "action_ata_product.hh"
#include "action_aat_product.hh"
#include "action_atv_product.hh"
#include "action_cholesky.hh"
#include "action_trisolve.hh"
BTL_MAIN;
int main()
{
bench_static<Action_axpy,eigen2_interface>();
bench_static<Action_matrix_matrix_product,eigen2_interface>();
bench_static<Action_matrix_vector_product,eigen2_interface>();
bench_static<Action_atv_product,eigen2_interface>();
bench_static<Action_cholesky,eigen2_interface>();
bench_static<Action_trisolve,eigen2_interface>();
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/eigen3/main_linear.cpp | .cpp | 1,285 | 36 | //=====================================================
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#include "utilities.h"
#include "eigen3_interface.hh"
#include "bench.hh"
#include "basic_actions.hh"
BTL_MAIN;
int main()
{
bench<Action_axpy<eigen3_interface<REAL_TYPE> > >(MIN_AXPY,MAX_AXPY,NB_POINT);
bench<Action_axpby<eigen3_interface<REAL_TYPE> > >(MIN_AXPY,MAX_AXPY,NB_POINT);
bench<Action_rot<eigen3_interface<REAL_TYPE> > >(MIN_AXPY,MAX_AXPY,NB_POINT);
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/eigen3/main_matmat.cpp | .cpp | 1,381 | 36 | //=====================================================
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#include "utilities.h"
#include "eigen3_interface.hh"
#include "bench.hh"
#include "basic_actions.hh"
BTL_MAIN;
int main()
{
bench<Action_matrix_matrix_product<eigen3_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
// bench<Action_ata_product<eigen3_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
bench<Action_aat_product<eigen3_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
bench<Action_trmm<eigen3_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/eigen3/main_adv.cpp | .cpp | 1,799 | 45 | //=====================================================
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#include "utilities.h"
#include "eigen3_interface.hh"
#include "bench.hh"
#include "action_trisolve.hh"
#include "action_trisolve_matrix.hh"
#include "action_cholesky.hh"
#include "action_hessenberg.hh"
#include "action_lu_decomp.hh"
#include "action_partial_lu.hh"
BTL_MAIN;
int main()
{
bench<Action_trisolve<eigen3_interface<REAL_TYPE> > >(MIN_LU,MAX_LU,NB_POINT);
bench<Action_trisolve_matrix<eigen3_interface<REAL_TYPE> > >(MIN_LU,MAX_LU,NB_POINT);
bench<Action_cholesky<eigen3_interface<REAL_TYPE> > >(MIN_LU,MAX_LU,NB_POINT);
// bench<Action_lu_decomp<eigen3_interface<REAL_TYPE> > >(MIN_LU,MAX_LU,NB_POINT);
bench<Action_partial_lu<eigen3_interface<REAL_TYPE> > >(MIN_LU,MAX_LU,NB_POINT);
// bench<Action_hessenberg<eigen3_interface<REAL_TYPE> > >(MIN_LU,MAX_LU,NB_POINT);
bench<Action_tridiagonalization<eigen3_interface<REAL_TYPE> > >(MIN_LU,MAX_LU,NB_POINT);
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/eigen3/eigen3_interface.hh | .hh | 8,077 | 241 | //=====================================================
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#ifndef EIGEN3_INTERFACE_HH
#define EIGEN3_INTERFACE_HH
#include <Eigen/Eigen>
#include <vector>
#include "btl.hh"
using namespace Eigen;
template<class real, int SIZE=Dynamic>
class eigen3_interface
{
public :
enum {IsFixedSize = (SIZE!=Dynamic)};
typedef real real_type;
typedef std::vector<real> stl_vector;
typedef std::vector<stl_vector> stl_matrix;
typedef Eigen::Matrix<real,SIZE,SIZE> gene_matrix;
typedef Eigen::Matrix<real,SIZE,1> gene_vector;
static inline std::string name( void )
{
return EIGEN_MAKESTRING(BTL_PREFIX);
}
static void free_matrix(gene_matrix & /*A*/, int /*N*/) {}
static void free_vector(gene_vector & /*B*/) {}
static BTL_DONT_INLINE void matrix_from_stl(gene_matrix & A, stl_matrix & A_stl){
A.resize(A_stl[0].size(), A_stl.size());
for (unsigned int j=0; j<A_stl.size() ; j++){
for (unsigned int i=0; i<A_stl[j].size() ; i++){
A.coeffRef(i,j) = A_stl[j][i];
}
}
}
static BTL_DONT_INLINE void vector_from_stl(gene_vector & B, stl_vector & B_stl){
B.resize(B_stl.size(),1);
for (unsigned int i=0; i<B_stl.size() ; i++){
B.coeffRef(i) = B_stl[i];
}
}
static BTL_DONT_INLINE void vector_to_stl(gene_vector & B, stl_vector & B_stl){
for (unsigned int i=0; i<B_stl.size() ; i++){
B_stl[i] = B.coeff(i);
}
}
static BTL_DONT_INLINE void matrix_to_stl(gene_matrix & A, stl_matrix & A_stl){
int N=A_stl.size();
for (int j=0;j<N;j++){
A_stl[j].resize(N);
for (int i=0;i<N;i++){
A_stl[j][i] = A.coeff(i,j);
}
}
}
static inline void matrix_matrix_product(const gene_matrix & A, const gene_matrix & B, gene_matrix & X, int /*N*/){
X.noalias() = A*B;
}
static inline void transposed_matrix_matrix_product(const gene_matrix & A, const gene_matrix & B, gene_matrix & X, int /*N*/){
X.noalias() = A.transpose()*B.transpose();
}
// static inline void ata_product(const gene_matrix & A, gene_matrix & X, int /*N*/){
// X.noalias() = A.transpose()*A;
// }
static inline void aat_product(const gene_matrix & A, gene_matrix & X, int /*N*/){
X.template triangularView<Lower>().setZero();
X.template selfadjointView<Lower>().rankUpdate(A);
}
static inline void matrix_vector_product(const gene_matrix & A, const gene_vector & B, gene_vector & X, int /*N*/){
X.noalias() = A*B;
}
static inline void symv(const gene_matrix & A, const gene_vector & B, gene_vector & X, int /*N*/){
X.noalias() = (A.template selfadjointView<Lower>() * B);
// internal::product_selfadjoint_vector<real,0,LowerTriangularBit,false,false>(N,A.data(),N, B.data(), 1, X.data(), 1);
}
template<typename Dest, typename Src> static void triassign(Dest& dst, const Src& src)
{
typedef typename Dest::Scalar Scalar;
typedef typename internal::packet_traits<Scalar>::type Packet;
const int PacketSize = sizeof(Packet)/sizeof(Scalar);
int size = dst.cols();
for(int j=0; j<size; j+=1)
{
// const int alignedEnd = alignedStart + ((innerSize-alignedStart) & ~packetAlignedMask);
Scalar* A0 = dst.data() + j*dst.stride();
int starti = j;
int alignedEnd = starti;
int alignedStart = (starti) + internal::first_aligned(&A0[starti], size-starti);
alignedEnd = alignedStart + ((size-alignedStart)/(2*PacketSize))*(PacketSize*2);
// do the non-vectorizable part of the assignment
for (int index = starti; index<alignedStart ; ++index)
{
if(Dest::Flags&RowMajorBit)
dst.copyCoeff(j, index, src);
else
dst.copyCoeff(index, j, src);
}
// do the vectorizable part of the assignment
for (int index = alignedStart; index<alignedEnd; index+=PacketSize)
{
if(Dest::Flags&RowMajorBit)
dst.template copyPacket<Src, Aligned, Unaligned>(j, index, src);
else
dst.template copyPacket<Src, Aligned, Unaligned>(index, j, src);
}
// do the non-vectorizable part of the assignment
for (int index = alignedEnd; index<size; ++index)
{
if(Dest::Flags&RowMajorBit)
dst.copyCoeff(j, index, src);
else
dst.copyCoeff(index, j, src);
}
//dst.col(j).tail(N-j) = src.col(j).tail(N-j);
}
}
static EIGEN_DONT_INLINE void syr2(gene_matrix & A, gene_vector & X, gene_vector & Y, int N){
// internal::product_selfadjoint_rank2_update<real,0,LowerTriangularBit>(N,A.data(),N, X.data(), 1, Y.data(), 1, -1);
for(int j=0; j<N; ++j)
A.col(j).tail(N-j) += X[j] * Y.tail(N-j) + Y[j] * X.tail(N-j);
}
static EIGEN_DONT_INLINE void ger(gene_matrix & A, gene_vector & X, gene_vector & Y, int N){
for(int j=0; j<N; ++j)
A.col(j) += X * Y[j];
}
static EIGEN_DONT_INLINE void rot(gene_vector & A, gene_vector & B, real c, real s, int /*N*/){
internal::apply_rotation_in_the_plane(A, B, JacobiRotation<real>(c,s));
}
static inline void atv_product(gene_matrix & A, gene_vector & B, gene_vector & X, int /*N*/){
X.noalias() = (A.transpose()*B);
}
static inline void axpy(real coef, const gene_vector & X, gene_vector & Y, int /*N*/){
Y += coef * X;
}
static inline void axpby(real a, const gene_vector & X, real b, gene_vector & Y, int /*N*/){
Y = a*X + b*Y;
}
static EIGEN_DONT_INLINE void copy_matrix(const gene_matrix & source, gene_matrix & cible, int /*N*/){
cible = source;
}
static EIGEN_DONT_INLINE void copy_vector(const gene_vector & source, gene_vector & cible, int /*N*/){
cible = source;
}
static inline void trisolve_lower(const gene_matrix & L, const gene_vector& B, gene_vector& X, int /*N*/){
X = L.template triangularView<Lower>().solve(B);
}
static inline void trisolve_lower_matrix(const gene_matrix & L, const gene_matrix& B, gene_matrix& X, int /*N*/){
X = L.template triangularView<Upper>().solve(B);
}
static inline void trmm(const gene_matrix & L, const gene_matrix& B, gene_matrix& X, int /*N*/){
X.noalias() = L.template triangularView<Lower>() * B;
}
static inline void cholesky(const gene_matrix & X, gene_matrix & C, int /*N*/){
C = X;
internal::llt_inplace<real,Lower>::blocked(C);
//C = X.llt().matrixL();
// C = X;
// Cholesky<gene_matrix>::computeInPlace(C);
// Cholesky<gene_matrix>::computeInPlaceBlock(C);
}
static inline void lu_decomp(const gene_matrix & X, gene_matrix & C, int /*N*/){
C = X.fullPivLu().matrixLU();
}
static inline void partial_lu_decomp(const gene_matrix & X, gene_matrix & C, int N){
Matrix<DenseIndex,1,Dynamic> piv(N);
DenseIndex nb;
C = X;
internal::partial_lu_inplace(C,piv,nb);
// C = X.partialPivLu().matrixLU();
}
static inline void tridiagonalization(const gene_matrix & X, gene_matrix & C, int N){
typename Tridiagonalization<gene_matrix>::CoeffVectorType aux(N-1);
C = X;
internal::tridiagonalization_inplace(C, aux);
}
static inline void hessenberg(const gene_matrix & X, gene_matrix & C, int /*N*/){
C = HessenbergDecomposition<gene_matrix>(X).packedMatrix();
}
};
#endif
| Unknown |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/blaze/blaze_interface.hh | .hh | 4,012 | 141 | //=====================================================
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#ifndef BLAZE_INTERFACE_HH
#define BLAZE_INTERFACE_HH
#include <blaze/Math.h>
#include <blaze/Blaze.h>
// using namespace blaze;
#include <vector>
template<class real>
class blaze_interface {
public :
typedef real real_type ;
typedef std::vector<real> stl_vector;
typedef std::vector<stl_vector > stl_matrix;
typedef blaze::DynamicMatrix<real,blaze::columnMajor> gene_matrix;
typedef blaze::DynamicVector<real> gene_vector;
static inline std::string name() { return "blaze"; }
static void free_matrix(gene_matrix & A, int N){
return ;
}
static void free_vector(gene_vector & B){
return ;
}
static inline void matrix_from_stl(gene_matrix & A, stl_matrix & A_stl){
A.resize(A_stl[0].size(), A_stl.size());
for (int j=0; j<A_stl.size() ; j++){
for (int i=0; i<A_stl[j].size() ; i++){
A(i,j) = A_stl[j][i];
}
}
}
static inline void vector_from_stl(gene_vector & B, stl_vector & B_stl){
B.resize(B_stl.size());
for (int i=0; i<B_stl.size() ; i++){
B[i] = B_stl[i];
}
}
static inline void vector_to_stl(gene_vector & B, stl_vector & B_stl){
for (int i=0; i<B_stl.size() ; i++){
B_stl[i] = B[i];
}
}
static inline void matrix_to_stl(gene_matrix & A, stl_matrix & A_stl){
int N=A_stl.size();
for (int j=0;j<N;j++){
A_stl[j].resize(N);
for (int i=0;i<N;i++){
A_stl[j][i] = A(i,j);
}
}
}
static inline void matrix_matrix_product(const gene_matrix & A, const gene_matrix & B, gene_matrix & X, int N){
X = (A*B);
}
static inline void transposed_matrix_matrix_product(const gene_matrix & A, const gene_matrix & B, gene_matrix & X, int N){
X = (trans(A)*trans(B));
}
static inline void ata_product(const gene_matrix & A, gene_matrix & X, int N){
X = (trans(A)*A);
}
static inline void aat_product(const gene_matrix & A, gene_matrix & X, int N){
X = (A*trans(A));
}
static inline void matrix_vector_product(gene_matrix & A, gene_vector & B, gene_vector & X, int N){
X = (A*B);
}
static inline void atv_product(gene_matrix & A, gene_vector & B, gene_vector & X, int N){
X = (trans(A)*B);
}
static inline void axpy(const real coef, const gene_vector & X, gene_vector & Y, int N){
Y += coef * X;
}
static inline void axpby(real a, const gene_vector & X, real b, gene_vector & Y, int N){
Y = a*X + b*Y;
}
// static inline void cholesky(const gene_matrix & X, gene_matrix & C, int N){
// C = X;
// recursive_cholesky(C);
// }
// static inline void lu_decomp(const gene_matrix & X, gene_matrix & R, int N){
// R = X;
// std::vector<int> ipvt(N);
// lu_factor(R, ipvt);
// }
// static inline void trisolve_lower(const gene_matrix & L, const gene_vector& B, gene_vector & X, int N){
// X = lower_trisolve(L, B);
// }
static inline void copy_matrix(const gene_matrix & source, gene_matrix & cible, int N){
cible = source;
}
static inline void copy_vector(const gene_vector & source, gene_vector & cible, int N){
cible = source;
}
};
#endif
| Unknown |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/blaze/main.cpp | .cpp | 1,645 | 41 | //=====================================================
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#include "utilities.h"
#include "blaze_interface.hh"
#include "bench.hh"
#include "basic_actions.hh"
BTL_MAIN;
int main()
{
bench<Action_axpy<blaze_interface<REAL_TYPE> > >(MIN_AXPY,MAX_AXPY,NB_POINT);
bench<Action_axpby<blaze_interface<REAL_TYPE> > >(MIN_AXPY,MAX_AXPY,NB_POINT);
bench<Action_matrix_vector_product<blaze_interface<REAL_TYPE> > >(MIN_MV,MAX_MV,NB_POINT);
bench<Action_atv_product<blaze_interface<REAL_TYPE> > >(MIN_MV,MAX_MV,NB_POINT);
// bench<Action_matrix_matrix_product<blaze_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
// bench<Action_ata_product<blaze_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
// bench<Action_aat_product<blaze_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/blitz/tiny_blitz_interface.hh | .hh | 3,100 | 107 | //=====================================================
// File : tiny_blitz_interface.hh
// Author : L. Plagne <laurent.plagne@edf.fr)>
// Copyright (C) EDF R&D, lun sep 30 14:23:30 CEST 2002
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#ifndef TINY_BLITZ_INTERFACE_HH
#define TINY_BLITZ_INTERFACE_HH
#include "blitz/array.h"
#include "blitz/tiny.h"
#include "blitz/tinymat.h"
#include "blitz/tinyvec.h"
#include <blitz/tinyvec-et.h>
#include <vector>
BZ_USING_NAMESPACE(blitz)
template<class real, int SIZE>
class tiny_blitz_interface
{
public :
typedef real real_type ;
typedef std::vector<real> stl_vector;
typedef std::vector<stl_vector > stl_matrix;
typedef TinyVector<real,SIZE> gene_vector;
typedef TinyMatrix<real,SIZE,SIZE> gene_matrix;
static inline std::string name() { return "tiny_blitz"; }
static void free_matrix(gene_matrix & A, int N){}
static void free_vector(gene_vector & B){}
static inline void matrix_from_stl(gene_matrix & A, stl_matrix & A_stl){
for (int j=0; j<A_stl.size() ; j++)
for (int i=0; i<A_stl[j].size() ; i++)
A(i,j)=A_stl[j][i];
}
static inline void vector_from_stl(gene_vector & B, stl_vector & B_stl){
for (int i=0; i<B_stl.size() ; i++)
B(i) = B_stl[i];
}
static inline void vector_to_stl(gene_vector & B, stl_vector & B_stl){
for (int i=0; i<B_stl.size() ; i++)
B_stl[i] = B(i);
}
static inline void matrix_to_stl(gene_matrix & A, stl_matrix & A_stl){
int N = A_stl.size();
for (int j=0;j<N;j++)
{
A_stl[j].resize(N);
for (int i=0;i<N;i++)
A_stl[j][i] = A(i,j);
}
}
static inline void copy_matrix(const gene_matrix & source, gene_matrix & cible, int N){
for (int j=0;j<N;j++)
for (int i=0;i<N;i++)
cible(i,j) = source(i,j);
}
static inline void copy_vector(const gene_vector & source, gene_vector & cible, int N){
for (int i=0;i<N;i++){
cible(i) = source(i);
}
}
static inline void matrix_matrix_product(const gene_matrix & A, const gene_matrix & B, gene_matrix & X, int N){
X = product(A,B);
}
static inline void matrix_vector_product(gene_matrix & A, gene_vector & B, gene_vector & X, int N){
X = product(A,B);
}
static inline void axpy(const real coef, const gene_vector & X, gene_vector & Y, int N){
Y += coef * X;
}
};
#endif
| Unknown |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/blitz/blitz_interface.hh | .hh | 4,129 | 148 | //=====================================================
// File : blitz_interface.hh
// Author : L. Plagne <laurent.plagne@edf.fr)>
// Copyright (C) EDF R&D, lun sep 30 14:23:30 CEST 2002
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#ifndef BLITZ_INTERFACE_HH
#define BLITZ_INTERFACE_HH
#include <blitz/blitz.h>
#include <blitz/array.h>
#include <blitz/vector-et.h>
#include <blitz/vecwhere.h>
#include <blitz/matrix.h>
#include <vector>
BZ_USING_NAMESPACE(blitz)
template<class real>
class blitz_interface{
public :
typedef real real_type ;
typedef std::vector<real> stl_vector;
typedef std::vector<stl_vector > stl_matrix;
typedef blitz::Array<real, 2> gene_matrix;
typedef blitz::Array<real, 1> gene_vector;
// typedef blitz::Matrix<real, blitz::ColumnMajor> gene_matrix;
// typedef blitz::Vector<real> gene_vector;
static inline std::string name() { return "blitz"; }
static void free_matrix(gene_matrix & A, int N){}
static void free_vector(gene_vector & B){}
static inline void matrix_from_stl(gene_matrix & A, stl_matrix & A_stl){
A.resize(A_stl[0].size(),A_stl.size());
for (int j=0; j<A_stl.size() ; j++){
for (int i=0; i<A_stl[j].size() ; i++){
A(i,j)=A_stl[j][i];
}
}
}
static inline void vector_from_stl(gene_vector & B, stl_vector & B_stl){
B.resize(B_stl.size());
for (int i=0; i<B_stl.size() ; i++){
B(i)=B_stl[i];
}
}
static inline void vector_to_stl(gene_vector & B, stl_vector & B_stl){
for (int i=0; i<B_stl.size() ; i++){
B_stl[i]=B(i);
}
}
static inline void matrix_to_stl(gene_matrix & A, stl_matrix & A_stl){
int N=A_stl.size();
for (int j=0;j<N;j++){
A_stl[j].resize(N);
for (int i=0;i<N;i++)
A_stl[j][i] = A(i,j);
}
}
static inline void matrix_matrix_product(const gene_matrix & A, const gene_matrix & B, gene_matrix & X, int N)
{
firstIndex i;
secondIndex j;
thirdIndex k;
X = sum(A(i,k) * B(k,j), k);
}
static inline void ata_product(const gene_matrix & A, gene_matrix & X, int N)
{
firstIndex i;
secondIndex j;
thirdIndex k;
X = sum(A(k,i) * A(k,j), k);
}
static inline void aat_product(const gene_matrix & A, gene_matrix & X, int N)
{
firstIndex i;
secondIndex j;
thirdIndex k;
X = sum(A(i,k) * A(j,k), k);
}
static inline void matrix_vector_product(gene_matrix & A, gene_vector & B, gene_vector & X, int N)
{
firstIndex i;
secondIndex j;
X = sum(A(i,j)*B(j),j);
}
static inline void atv_product(gene_matrix & A, gene_vector & B, gene_vector & X, int N)
{
firstIndex i;
secondIndex j;
X = sum(A(j,i) * B(j),j);
}
static inline void axpy(const real coef, const gene_vector & X, gene_vector & Y, int N)
{
firstIndex i;
Y = Y(i) + coef * X(i);
//Y += coef * X;
}
static inline void copy_matrix(const gene_matrix & source, gene_matrix & cible, int N){
cible = source;
//cible.template operator=<gene_matrix>(source);
// for (int i=0;i<N;i++){
// for (int j=0;j<N;j++){
// cible(i,j)=source(i,j);
// }
// }
}
static inline void copy_vector(const gene_vector & source, gene_vector & cible, int N){
//cible.template operator=<gene_vector>(source);
cible = source;
}
};
#endif
| Unknown |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/blitz/blitz_LU_solve_interface.hh | .hh | 5,364 | 193 | //=====================================================
// File : blitz_LU_solve_interface.hh
// Author : L. Plagne <laurent.plagne@edf.fr)>
// Copyright (C) EDF R&D, lun sep 30 14:23:31 CEST 2002
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#ifndef BLITZ_LU_SOLVE_INTERFACE_HH
#define BLITZ_LU_SOLVE_INTERFACE_HH
#include "blitz/array.h"
#include <vector>
BZ_USING_NAMESPACE(blitz)
template<class real>
class blitz_LU_solve_interface : public blitz_interface<real>
{
public :
typedef typename blitz_interface<real>::gene_matrix gene_matrix;
typedef typename blitz_interface<real>::gene_vector gene_vector;
typedef blitz::Array<int,1> Pivot_Vector;
inline static void new_Pivot_Vector(Pivot_Vector & pivot,int N)
{
pivot.resize(N);
}
inline static void free_Pivot_Vector(Pivot_Vector & pivot)
{
return;
}
static inline real matrix_vector_product_sliced(const gene_matrix & A, gene_vector B, int row, int col_start, int col_end)
{
real somme=0.;
for (int j=col_start ; j<col_end+1 ; j++){
somme+=A(row,j)*B(j);
}
return somme;
}
static inline real matrix_matrix_product_sliced(gene_matrix & A, int row, int col_start, int col_end, gene_matrix & B, int row_shift, int col )
{
real somme=0.;
for (int j=col_start ; j<col_end+1 ; j++){
somme+=A(row,j)*B(j+row_shift,col);
}
return somme;
}
inline static void LU_factor(gene_matrix & LU, Pivot_Vector & pivot, int N)
{
ASSERT( LU.rows()==LU.cols() ) ;
int index_max = 0 ;
real big = 0. ;
real theSum = 0. ;
real dum = 0. ;
// Get the implicit scaling information :
gene_vector ImplicitScaling( N ) ;
for( int i=0; i<N; i++ ) {
big = 0. ;
for( int j=0; j<N; j++ ) {
if( abs( LU( i, j ) )>=big ) big = abs( LU( i, j ) ) ;
}
if( big==0. ) {
INFOS( "blitz_LU_factor::Singular matrix" ) ;
exit( 0 ) ;
}
ImplicitScaling( i ) = 1./big ;
}
// Loop over columns of Crout's method :
for( int j=0; j<N; j++ ) {
for( int i=0; i<j; i++ ) {
theSum = LU( i, j ) ;
theSum -= matrix_matrix_product_sliced(LU, i, 0, i-1, LU, 0, j) ;
// theSum -= sum( LU( i, Range( fromStart, i-1 ) )*LU( Range( fromStart, i-1 ), j ) ) ;
LU( i, j ) = theSum ;
}
// Search for the largest pivot element :
big = 0. ;
for( int i=j; i<N; i++ ) {
theSum = LU( i, j ) ;
theSum -= matrix_matrix_product_sliced(LU, i, 0, j-1, LU, 0, j) ;
// theSum -= sum( LU( i, Range( fromStart, j-1 ) )*LU( Range( fromStart, j-1 ), j ) ) ;
LU( i, j ) = theSum ;
if( (ImplicitScaling( i )*abs( theSum ))>=big ) {
dum = ImplicitScaling( i )*abs( theSum ) ;
big = dum ;
index_max = i ;
}
}
// Interchanging rows and the scale factor :
if( j!=index_max ) {
for( int k=0; k<N; k++ ) {
dum = LU( index_max, k ) ;
LU( index_max, k ) = LU( j, k ) ;
LU( j, k ) = dum ;
}
ImplicitScaling( index_max ) = ImplicitScaling( j ) ;
}
pivot( j ) = index_max ;
if ( LU( j, j )==0. ) LU( j, j ) = 1.e-20 ;
// Divide by the pivot element :
if( j<N ) {
dum = 1./LU( j, j ) ;
for( int i=j+1; i<N; i++ ) LU( i, j ) *= dum ;
}
}
}
inline static void LU_solve(const gene_matrix & LU, const Pivot_Vector pivot, gene_vector &B, gene_vector X, int N)
{
// Pour conserver le meme header, on travaille sur X, copie du second-membre B
X = B.copy() ;
ASSERT( LU.rows()==LU.cols() ) ;
firstIndex indI ;
// Forward substitution :
int ii = 0 ;
real theSum = 0. ;
for( int i=0; i<N; i++ ) {
int ip = pivot( i ) ;
theSum = X( ip ) ;
// theSum = B( ip ) ;
X( ip ) = X( i ) ;
// B( ip ) = B( i ) ;
if( ii ) {
theSum -= matrix_vector_product_sliced(LU, X, i, ii-1, i-1) ;
// theSum -= sum( LU( i, Range( ii-1, i-1 ) )*X( Range( ii-1, i-1 ) ) ) ;
// theSum -= sum( LU( i, Range( ii-1, i-1 ) )*B( Range( ii-1, i-1 ) ) ) ;
} else if( theSum ) {
ii = i+1 ;
}
X( i ) = theSum ;
// B( i ) = theSum ;
}
// Backsubstitution :
for( int i=N-1; i>=0; i-- ) {
theSum = X( i ) ;
// theSum = B( i ) ;
theSum -= matrix_vector_product_sliced(LU, X, i, i+1, N) ;
// theSum -= sum( LU( i, Range( i+1, toEnd ) )*X( Range( i+1, toEnd ) ) ) ;
// theSum -= sum( LU( i, Range( i+1, toEnd ) )*B( Range( i+1, toEnd ) ) ) ;
// Store a component of the solution vector :
X( i ) = theSum/LU( i, i ) ;
// B( i ) = theSum/LU( i, i ) ;
}
}
};
#endif
| Unknown |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/blitz/btl_blitz.cpp | .cpp | 1,962 | 52 | //=====================================================
// File : main.cpp
// Author : L. Plagne <laurent.plagne@edf.fr)>
// Copyright (C) EDF R&D, lun sep 30 14:23:30 CEST 2002
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#include "utilities.h"
#include "blitz_interface.hh"
#include "blitz_LU_solve_interface.hh"
#include "bench.hh"
#include "action_matrix_vector_product.hh"
#include "action_matrix_matrix_product.hh"
#include "action_axpy.hh"
#include "action_lu_solve.hh"
#include "action_ata_product.hh"
#include "action_aat_product.hh"
#include "action_atv_product.hh"
BTL_MAIN;
int main()
{
bench<Action_matrix_vector_product<blitz_interface<REAL_TYPE> > >(MIN_MV,MAX_MV,NB_POINT);
bench<Action_atv_product<blitz_interface<REAL_TYPE> > >(MIN_MV,MAX_MV,NB_POINT);
bench<Action_matrix_matrix_product<blitz_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
bench<Action_ata_product<blitz_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
bench<Action_aat_product<blitz_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
bench<Action_axpy<blitz_interface<REAL_TYPE> > >(MIN_AXPY,MAX_AXPY,NB_POINT);
//bench<Action_lu_solve<blitz_LU_solve_interface<REAL_TYPE> > >(MIN_LU,MAX_LU,NB_POINT);
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/blitz/btl_tiny_blitz.cpp | .cpp | 1,393 | 39 | //=====================================================
// File : main.cpp
// Author : L. Plagne <laurent.plagne@edf.fr)>
// Copyright (C) EDF R&D, lun sep 30 14:23:30 CEST 2002
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#include "utilities.h"
#include "tiny_blitz_interface.hh"
#include "static/bench_static.hh"
#include "action_matrix_vector_product.hh"
#include "action_matrix_matrix_product.hh"
#include "action_axpy.hh"
BTL_MAIN;
int main()
{
bench_static<Action_axpy,tiny_blitz_interface>();
bench_static<Action_matrix_matrix_product,tiny_blitz_interface>();
bench_static<Action_matrix_vector_product,tiny_blitz_interface>();
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/eigen2/main_vecmat.cpp | .cpp | 1,456 | 37 | //=====================================================
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#include "utilities.h"
#include "eigen2_interface.hh"
#include "bench.hh"
#include "basic_actions.hh"
BTL_MAIN;
int main()
{
bench<Action_matrix_vector_product<eigen2_interface<REAL_TYPE> > >(MIN_MV,MAX_MV,NB_POINT);
bench<Action_atv_product<eigen2_interface<REAL_TYPE> > >(MIN_MV,MAX_MV,NB_POINT);
// bench<Action_symv<eigen2_interface<REAL_TYPE> > >(MIN_MV,MAX_MV,NB_POINT);
// bench<Action_syr2<eigen2_interface<REAL_TYPE> > >(MIN_MV,MAX_MV,NB_POINT);
// bench<Action_ger<eigen2_interface<REAL_TYPE> > >(MIN_MV,MAX_MV,NB_POINT);
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/eigen2/eigen2_interface.hh | .hh | 5,151 | 169 | //=====================================================
// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#ifndef EIGEN2_INTERFACE_HH
#define EIGEN2_INTERFACE_HH
// #include <cblas.h>
#include <Eigen/Core>
#include <Eigen/Cholesky>
#include <Eigen/LU>
#include <Eigen/QR>
#include <vector>
#include "btl.hh"
using namespace Eigen;
template<class real, int SIZE=Dynamic>
class eigen2_interface
{
public :
enum {IsFixedSize = (SIZE!=Dynamic)};
typedef real real_type;
typedef std::vector<real> stl_vector;
typedef std::vector<stl_vector> stl_matrix;
typedef Eigen::Matrix<real,SIZE,SIZE> gene_matrix;
typedef Eigen::Matrix<real,SIZE,1> gene_vector;
static inline std::string name( void )
{
#if defined(EIGEN_VECTORIZE_SSE)
if (SIZE==Dynamic) return "eigen2"; else return "tiny_eigen2";
#elif defined(EIGEN_VECTORIZE_ALTIVEC) || defined(EIGEN_VECTORIZE_VSX)
if (SIZE==Dynamic) return "eigen2"; else return "tiny_eigen2";
#else
if (SIZE==Dynamic) return "eigen2_novec"; else return "tiny_eigen2_novec";
#endif
}
static void free_matrix(gene_matrix & A, int N) {}
static void free_vector(gene_vector & B) {}
static BTL_DONT_INLINE void matrix_from_stl(gene_matrix & A, stl_matrix & A_stl){
A.resize(A_stl[0].size(), A_stl.size());
for (int j=0; j<A_stl.size() ; j++){
for (int i=0; i<A_stl[j].size() ; i++){
A.coeffRef(i,j) = A_stl[j][i];
}
}
}
static BTL_DONT_INLINE void vector_from_stl(gene_vector & B, stl_vector & B_stl){
B.resize(B_stl.size(),1);
for (int i=0; i<B_stl.size() ; i++){
B.coeffRef(i) = B_stl[i];
}
}
static BTL_DONT_INLINE void vector_to_stl(gene_vector & B, stl_vector & B_stl){
for (int i=0; i<B_stl.size() ; i++){
B_stl[i] = B.coeff(i);
}
}
static BTL_DONT_INLINE void matrix_to_stl(gene_matrix & A, stl_matrix & A_stl){
int N=A_stl.size();
for (int j=0;j<N;j++){
A_stl[j].resize(N);
for (int i=0;i<N;i++){
A_stl[j][i] = A.coeff(i,j);
}
}
}
static inline void matrix_matrix_product(const gene_matrix & A, const gene_matrix & B, gene_matrix & X, int N){
X = (A*B).lazy();
}
static inline void transposed_matrix_matrix_product(const gene_matrix & A, const gene_matrix & B, gene_matrix & X, int N){
X = (A.transpose()*B.transpose()).lazy();
}
static inline void ata_product(const gene_matrix & A, gene_matrix & X, int N){
X = (A.transpose()*A).lazy();
}
static inline void aat_product(const gene_matrix & A, gene_matrix & X, int N){
X = (A*A.transpose()).lazy();
}
static inline void matrix_vector_product(const gene_matrix & A, const gene_vector & B, gene_vector & X, int N){
X = (A*B)/*.lazy()*/;
}
static inline void atv_product(gene_matrix & A, gene_vector & B, gene_vector & X, int N){
X = (A.transpose()*B)/*.lazy()*/;
}
static inline void axpy(real coef, const gene_vector & X, gene_vector & Y, int N){
Y += coef * X;
}
static inline void axpby(real a, const gene_vector & X, real b, gene_vector & Y, int N){
Y = a*X + b*Y;
}
static inline void copy_matrix(const gene_matrix & source, gene_matrix & cible, int N){
cible = source;
}
static inline void copy_vector(const gene_vector & source, gene_vector & cible, int N){
cible = source;
}
static inline void trisolve_lower(const gene_matrix & L, const gene_vector& B, gene_vector& X, int N){
X = L.template marked<LowerTriangular>().solveTriangular(B);
}
static inline void trisolve_lower_matrix(const gene_matrix & L, const gene_matrix& B, gene_matrix& X, int N){
X = L.template marked<LowerTriangular>().solveTriangular(B);
}
static inline void cholesky(const gene_matrix & X, gene_matrix & C, int N){
C = X.llt().matrixL();
// C = X;
// Cholesky<gene_matrix>::computeInPlace(C);
// Cholesky<gene_matrix>::computeInPlaceBlock(C);
}
static inline void lu_decomp(const gene_matrix & X, gene_matrix & C, int N){
C = X.lu().matrixLU();
// C = X.inverse();
}
static inline void tridiagonalization(const gene_matrix & X, gene_matrix & C, int N){
C = Tridiagonalization<gene_matrix>(X).packedMatrix();
}
static inline void hessenberg(const gene_matrix & X, gene_matrix & C, int N){
C = HessenbergDecomposition<gene_matrix>(X).packedMatrix();
}
};
#endif
| Unknown |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/eigen2/main_linear.cpp | .cpp | 1,205 | 35 | //=====================================================
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#include "utilities.h"
#include "eigen2_interface.hh"
#include "bench.hh"
#include "basic_actions.hh"
BTL_MAIN;
int main()
{
bench<Action_axpy<eigen2_interface<REAL_TYPE> > >(MIN_AXPY,MAX_AXPY,NB_POINT);
bench<Action_axpby<eigen2_interface<REAL_TYPE> > >(MIN_AXPY,MAX_AXPY,NB_POINT);
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/eigen2/main_matmat.cpp | .cpp | 1,384 | 36 | //=====================================================
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#include "utilities.h"
#include "eigen2_interface.hh"
#include "bench.hh"
#include "basic_actions.hh"
BTL_MAIN;
int main()
{
bench<Action_matrix_matrix_product<eigen2_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
// bench<Action_ata_product<eigen2_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
bench<Action_aat_product<eigen2_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
// bench<Action_trmm<eigen2_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/eigen2/btl_tiny_eigen2.cpp | .cpp | 1,664 | 47 | //=====================================================
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#include "utilities.h"
#include "eigen3_interface.hh"
#include "static/bench_static.hh"
#include "action_matrix_vector_product.hh"
#include "action_matrix_matrix_product.hh"
#include "action_axpy.hh"
#include "action_lu_solve.hh"
#include "action_ata_product.hh"
#include "action_aat_product.hh"
#include "action_atv_product.hh"
#include "action_cholesky.hh"
#include "action_trisolve.hh"
BTL_MAIN;
int main()
{
bench_static<Action_axpy,eigen2_interface>();
bench_static<Action_matrix_matrix_product,eigen2_interface>();
bench_static<Action_matrix_vector_product,eigen2_interface>();
bench_static<Action_atv_product,eigen2_interface>();
bench_static<Action_cholesky,eigen2_interface>();
bench_static<Action_trisolve,eigen2_interface>();
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/libs/eigen2/main_adv.cpp | .cpp | 1,799 | 45 | //=====================================================
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#include "utilities.h"
#include "eigen2_interface.hh"
#include "bench.hh"
#include "action_trisolve.hh"
#include "action_trisolve_matrix.hh"
#include "action_cholesky.hh"
#include "action_hessenberg.hh"
#include "action_lu_decomp.hh"
// #include "action_partial_lu.hh"
BTL_MAIN;
int main()
{
bench<Action_trisolve<eigen2_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
bench<Action_trisolve_matrix<eigen2_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
bench<Action_cholesky<eigen2_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
bench<Action_lu_decomp<eigen2_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
// bench<Action_partial_lu<eigen2_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
bench<Action_hessenberg<eigen2_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
bench<Action_tridiagonalization<eigen2_interface<REAL_TYPE> > >(MIN_MM,MAX_MM,NB_POINT);
return 0;
}
| C++ |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/actions/action_symv.hh | .hh | 3,691 | 140 | //=====================================================
// File : action_symv.hh
// Author : L. Plagne <laurent.plagne@edf.fr)>
// Copyright (C) EDF R&D, lun sep 30 14:23:19 CEST 2002
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#ifndef ACTION_SYMV
#define ACTION_SYMV
#include "utilities.h"
#include "STL_interface.hh"
#include <string>
#include "init/init_function.hh"
#include "init/init_vector.hh"
#include "init/init_matrix.hh"
using namespace std;
template<class Interface>
class Action_symv {
public :
// Ctor
BTL_DONT_INLINE Action_symv( int size ):_size(size)
{
MESSAGE("Action_symv Ctor");
// STL matrix and vector initialization
init_matrix_symm<pseudo_random>(A_stl,_size);
init_vector<pseudo_random>(B_stl,_size);
init_vector<null_function>(X_stl,_size);
init_vector<null_function>(resu_stl,_size);
// generic matrix and vector initialization
Interface::matrix_from_stl(A_ref,A_stl);
Interface::matrix_from_stl(A,A_stl);
Interface::vector_from_stl(B_ref,B_stl);
Interface::vector_from_stl(B,B_stl);
Interface::vector_from_stl(X_ref,X_stl);
Interface::vector_from_stl(X,X_stl);
}
// invalidate copy ctor
Action_symv( const Action_symv & )
{
INFOS("illegal call to Action_symv Copy Ctor");
exit(1);
}
// Dtor
BTL_DONT_INLINE ~Action_symv( void ){
Interface::free_matrix(A,_size);
Interface::free_vector(B);
Interface::free_vector(X);
Interface::free_matrix(A_ref,_size);
Interface::free_vector(B_ref);
Interface::free_vector(X_ref);
}
// action name
static inline std::string name( void )
{
return "symv_" + Interface::name();
}
double nb_op_base( void ){
return 2.0*_size*_size;
}
BTL_DONT_INLINE void initialize( void ){
Interface::copy_matrix(A_ref,A,_size);
Interface::copy_vector(B_ref,B,_size);
Interface::copy_vector(X_ref,X,_size);
}
BTL_DONT_INLINE void calculate( void ) {
BTL_ASM_COMMENT("#begin symv");
Interface::symv(A,B,X,_size);
BTL_ASM_COMMENT("end symv");
}
BTL_DONT_INLINE void check_result( void ){
if (_size>128) return;
// calculation check
Interface::vector_to_stl(X,resu_stl);
STL_interface<typename Interface::real_type>::symv(A_stl,B_stl,X_stl,_size);
typename Interface::real_type error=
STL_interface<typename Interface::real_type>::norm_diff(X_stl,resu_stl);
if (error>1.e-5){
INFOS("WRONG CALCULATION...residual=" << error);
exit(0);
}
}
private :
typename Interface::stl_matrix A_stl;
typename Interface::stl_vector B_stl;
typename Interface::stl_vector X_stl;
typename Interface::stl_vector resu_stl;
typename Interface::gene_matrix A_ref;
typename Interface::gene_vector B_ref;
typename Interface::gene_vector X_ref;
typename Interface::gene_matrix A;
typename Interface::gene_vector B;
typename Interface::gene_vector X;
int _size;
};
#endif
| Unknown |
2D | JaeHyunLee94/mpm2d | external/eigen-3.3.9/bench/btl/actions/action_trisolve_matrix.hh | .hh | 4,061 | 166 | //=====================================================
// File : action_matrix_matrix_product.hh
// Author : L. Plagne <laurent.plagne@edf.fr)>
// Copyright (C) EDF R&D, lun sep 30 14:23:19 CEST 2002
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
//
#ifndef ACTION_TRISOLVE_MATRIX_PRODUCT
#define ACTION_TRISOLVE_MATRIX_PRODUCT
#include "utilities.h"
#include "STL_interface.hh"
#include <string>
#include "init/init_function.hh"
#include "init/init_vector.hh"
#include "init/init_matrix.hh"
using namespace std;
template<class Interface>
class Action_trisolve_matrix {
public :
// Ctor
Action_trisolve_matrix( int size ):_size(size)
{
MESSAGE("Action_trisolve_matrix Ctor");
// STL matrix and vector initialization
init_matrix<pseudo_random>(A_stl,_size);
init_matrix<pseudo_random>(B_stl,_size);
init_matrix<null_function>(X_stl,_size);
init_matrix<null_function>(resu_stl,_size);
for (int j=0; j<_size; ++j)
{
for (int i=0; i<j; ++i)
A_stl[j][i] = 0;
A_stl[j][j] += 3;
}
// generic matrix and vector initialization
Interface::matrix_from_stl(A_ref,A_stl);
Interface::matrix_from_stl(B_ref,B_stl);
Interface::matrix_from_stl(X_ref,X_stl);
Interface::matrix_from_stl(A,A_stl);
Interface::matrix_from_stl(B,B_stl);
Interface::matrix_from_stl(X,X_stl);
_cost = 0;
for (int j=0; j<_size; ++j)
{
_cost += 2*j + 1;
}
_cost *= _size;
}
// invalidate copy ctor
Action_trisolve_matrix( const Action_trisolve_matrix & )
{
INFOS("illegal call to Action_trisolve_matrix Copy Ctor");
exit(0);
}
// Dtor
~Action_trisolve_matrix( void ){
MESSAGE("Action_trisolve_matrix Dtor");
// deallocation
Interface::free_matrix(A,_size);
Interface::free_matrix(B,_size);
Interface::free_matrix(X,_size);
Interface::free_matrix(A_ref,_size);
Interface::free_matrix(B_ref,_size);
Interface::free_matrix(X_ref,_size);
}
// action name
static inline std::string name( void )
{
return "trisolve_matrix_"+Interface::name();
}
double nb_op_base( void ){
return _cost;
}
inline void initialize( void ){
Interface::copy_matrix(A_ref,A,_size);
Interface::copy_matrix(B_ref,B,_size);
Interface::copy_matrix(X_ref,X,_size);
}
inline void calculate( void ) {
Interface::trisolve_lower_matrix(A,B,X,_size);
}
void check_result( void ){
// calculation check
// Interface::matrix_to_stl(X,resu_stl);
//
// STL_interface<typename Interface::real_type>::matrix_matrix_product(A_stl,B_stl,X_stl,_size);
//
// typename Interface::real_type error=
// STL_interface<typename Interface::real_type>::norm_diff(X_stl,resu_stl);
//
// if (error>1.e-6){
// INFOS("WRONG CALCULATION...residual=" << error);
// // exit(1);
// }
}
private :
typename Interface::stl_matrix A_stl;
typename Interface::stl_matrix B_stl;
typename Interface::stl_matrix X_stl;
typename Interface::stl_matrix resu_stl;
typename Interface::gene_matrix A_ref;
typename Interface::gene_matrix B_ref;
typename Interface::gene_matrix X_ref;
typename Interface::gene_matrix A;
typename Interface::gene_matrix B;
typename Interface::gene_matrix X;
int _size;
double _cost;
};
#endif
| Unknown |
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