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# GPU worker, phase 1: build ggml with CUDA and execute the real IQ2_XXS/Q2_K expert blocks on the card.
#
# Image: a CUDA devel image (nvcc required). Input preference:
# 1. the mounted safetensors artifact (needs the Runpod network volume, which is
# datacenter-local and single-attach),
# 2. a packed GGUF already in the workspace,
# 3. the first published GGUF shard from Hugging Face (works on any DC).
set -uo pipefail
trap 'echo "gpu-kernel aborted rc=$? at line $LINENO"' ERR
STAMP=$(date -u +%Y%m%dT%H%M%SZ)
WORK=${WORK:-/workspace/v41-quant}
LOGDIR=$WORK/logs; mkdir -p "$LOGDIR"
exec > >(tee -a "$LOGDIR/gpu-kernel-$STAMP.log") 2>&1
ARCH=${CUDA_ARCH:-100a}
EVIDENCE_REPO=${EVIDENCE_REPO:-apetersson/v41-quant-worker}
GGUF_REPO=${GGUF_REPO:-apetersson/DeepSeek-V4.1-Flash-MixedQ2-GGUF}
BUNDLE=${BUNDLE:-v41-runtimes-20260910T1240.tgz}
ARTIFACT=${ARTIFACT:-$WORK/q2-iq2-20260910}
OUT=${OUT:-$WORK/gpu-kernel-$STAMP}
mkdir -p "$OUT"
echo "=== gpu kernel worker $STAMP arch=$ARCH work=$WORK"
nvidia-smi -L || echo "no GPU visible"
nvidia-smi --query-gpu=name,memory.total,compute_cap --format=csv,noheader || true
export DEBIAN_FRONTEND=noninteractive
apt-get update -qq && apt-get install -y -qq --no-install-recommends \
git cmake g++ make ca-certificates curl python3-pip >/tmp/apt.log 2>&1
python3 -m pip install --quiet --no-cache-dir --break-system-packages numpy pyyaml tqdm huggingface_hub
if [ -f "$WORK/scripts/v41_quant_kernel_smoke.py" ]; then
echo "--- code already staged in $WORK (no HF fetch on the GPU host)"
else
curl -fsSL --retry 10 --retry-delay 20 --retry-all-errors -H "Authorization: Bearer ${HF_TOKEN:-}" \
-o /tmp/runtimes.tgz "https://huggingface.co/datasets/$EVIDENCE_REPO/resolve/main/$BUNDLE" \
&& tar xzf /tmp/runtimes.tgz -C "$WORK" --warning=no-unknown-keyword
fi
SCRIPTS="$WORK/scripts"
LLAMA=/opt/llama.cpp
rm -rf "$LLAMA"; mkdir -p "$LLAMA"; git -C "$LLAMA" init -q .
git -C "$LLAMA" remote add origin https://github.com/ggml-org/llama.cpp.git
git -C "$LLAMA" fetch -q --depth 1 origin refs/pull/28696/head
git -C "$LLAMA" checkout -q FETCH_HEAD
echo "llama.cpp: $(git -C "$LLAMA" log --oneline -1)"
export PYTHONPATH="$LLAMA/gguf-py"
echo "--- building ggml with CUDA (arch $ARCH)"
cmake -S "$LLAMA" -B "$LLAMA/build" -DCMAKE_BUILD_TYPE=Release -DGGML_CUDA=ON -DGGML_NATIVE=OFF \
-DCMAKE_CUDA_ARCHITECTURES="$ARCH" -DBUILD_SHARED_LIBS=ON -DLLAMA_BUILD_TESTS=OFF \
-DLLAMA_BUILD_EXAMPLES=OFF -DLLAMA_BUILD_TOOLS=OFF -DLLAMA_BUILD_SERVER=OFF >"$OUT/cmake.log" 2>&1
cmake --build "$LLAMA/build" --target ggml -j"$(nproc)" >"$OUT/ggml-cuda-build.log" 2>&1
echo "ggml cuda build rc=$?"
cc -O2 "$WORK/runtimes/v41-quant/ggml-cuda-smoke/kernel_smoke.c" -o /usr/local/bin/kernel_smoke \
-I"$LLAMA/ggml/include" -L"$LLAMA/build/bin" -lggml -lggml-base -lggml-cpu \
-Wl,-rpath,"$LLAMA/build/bin"
echo "harness compile rc=$?"
# Input selection -------------------------------------------------------------
SMOKE_INPUT=()
if [ -f "$ARTIFACT/plan.json" ]; then
SMOKE_INPUT=(--artifact "$ARTIFACT"); echo "--- input: mounted artifact"
else
EXISTING=$(ls -d "$WORK"/gguf-publish "$WORK"/gguf-mixedq2 2>/dev/null | head -1 || true)
if [ -n "$EXISTING" ] && ls "$EXISTING"/*.gguf >/dev/null 2>&1; then
SMOKE_INPUT=(--gguf "$EXISTING"); echo "--- input: workspace GGUF $EXISTING"
else
echo "--- input: waiting for the first GGUF shard of $GGUF_REPO"
GGUF_DIR="$WORK/gguf-remote"; mkdir -p "$GGUF_DIR"
for attempt in $(seq 1 80); do
if python3 - "$GGUF_REPO" "$GGUF_DIR" <<'PYEOF'
import os, sys
from huggingface_hub import HfApi, hf_hub_download
repo, dest = sys.argv[1:3]
files = sorted(f for f in HfApi(token=os.environ.get("HF_TOKEN")).list_repo_files(repo) if f.endswith(".gguf"))
if not files:
print("no shard published yet"); sys.exit(1)
hf_hub_download(repo, files[0], local_dir=dest, token=os.environ.get("HF_TOKEN"))
print("downloaded", files[0])
PYEOF
then break; fi
sleep 30
done
SMOKE_INPUT=(--gguf "$GGUF_DIR")
fi
fi
echo "--- kernel smoke on real blocks"
python3 "$SCRIPTS/v41_quant_kernel_smoke.py" "${SMOKE_INPUT[@]}" \
--kernel-bin /usr/local/bin/kernel_smoke --tensors 6 \
--json "$OUT/kernel-smoke-cuda.json" 2>&1 | tee "$OUT/kernel-smoke-cuda.txt"
KERNEL_RC=${PIPESTATUS[0]}
python3 - "$OUT" <<'PYEOF'
import json, os, sys
out = sys.argv[1]
path = os.path.join(out, "kernel-smoke-cuda.json")
if not os.path.exists(path):
print(json.dumps({"status": "no result file"})); raise SystemExit(0)
rec = json.load(open(path))
print(json.dumps({
"kernel_agrees": rec.get("kernel_agrees_with_dequantised_reference"),
"cosines": [t.get("cosine_vs_reference") for t in rec["tensors"]],
"rel_rms": [t.get("relative_rms_vs_reference") for t in rec["tensors"]],
"bandwidth_GiB_s": [t.get("weight_bandwidth_GiB_per_s") for t in rec["tensors"]],
}, indent=1))
PYEOF
# which backend actually ran (a silent CPU fallback must not be read as a GPU result)
grep -h "backend:" "$OUT"/kernel-smoke-cuda.txt 2>/dev/null | sort -u || true
if [ -n "${HF_TOKEN:-}" ]; then
for f in "$OUT/kernel-smoke-cuda.json" "$OUT/kernel-smoke-cuda.txt" \
"$OUT/ggml-cuda-build.log" "$LOGDIR/gpu-kernel-$STAMP.log"; do
[ -f "$f" ] || continue
python3 - "$f" "$EVIDENCE_REPO" "$STAMP" <<'PYEOF'
import os, sys
from huggingface_hub import HfApi
path, repo, stamp = sys.argv[1:4]
HfApi(token=os.environ["HF_TOKEN"]).upload_file(
path_or_fileobj=path, path_in_repo=f"runs/{stamp}/gpu-{os.path.basename(path)}",
repo_id=repo, repo_type="dataset", commit_message=f"gpu kernel evidence {os.path.basename(path)}")
print("pushed", os.path.basename(path))
PYEOF
done
fi
echo "=== gpu kernel worker finished rc=$KERNEL_RC"
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