Download README.md from bcui2/HPC-Bench: direct link, hf CLI and curl.
- Browser
- Download file 1.72 kB
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https://huggingface.co/datasets/bcui2/HPC-Bench/resolve/main/README.md
- Command line
-
hf download hf://datasets/bcui2/HPC-Bench/README.md
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curl -L -o README.md https://huggingface.co/datasets/bcui2/HPC-Bench/resolve/main/README.md
pretty_name: HPC-Bench Input Data
license: other
license_name: upstream-benchmark-licenses
tags:
- hpc
- benchmark
- code-optimization
- llm-evaluation
- openmp
- cuda
size_categories:
- n<1K
HPC-Bench Input Data
Input datasets for HPC-Bench: A Comprehensive Benchmark for High Performance Computing Codes (NeurIPS 2026 Evaluations and Datasets Track).
Code, benchmarks, and evaluation pipeline: https://github.com/Deep-Learning-Profiling-Tools/HPC-Bench
Contents
One zip archive per (setting, benchmark), each containing the benchmark's input_data/ directory with all five standardized input scales (mini, small, medium, large, extra-large).
| Path | Setting | Archives |
|---|---|---|
input_data/EX1/<benchmark>.zip |
Serial CPU optimization | 92 |
input_data/EX2/<benchmark>.zip |
OpenMP CPU parallelization | 92 |
input_data/EX3/<benchmark>.zip |
CUDA GPU optimization | 23 |
manifest.csv lists every archive with its size and SHA-256 checksum. The EX3 nn benchmark generates its input at run time and has no archive.
Download
Do not download these files by hand. From a clone of the GitHub repository, one command downloads the archives, verifies their checksums, and extracts each one into EX*/<benchmark>/input_data/:
python tools/fetch_input_data.py # everything (~38 GB zipped)
python tools/fetch_input_data.py --ex EX1 # one setting
python tools/fetch_input_data.py --benchmarks 2mm,bfs # selected benchmarks
License
The input data are derived from the upstream benchmark suites (PolyBench, Rodinia, Parboil, MachSuite, MiBench, PARSEC, and Codee) and remain subject to their respective licenses.