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2 changes: 1 addition & 1 deletion .github/workflows/flash_attention.yml
Original file line number Diff line number Diff line change
Expand Up @@ -60,7 +60,7 @@ jobs:
pushd fa4
python setup.py install
pip install -e flash_attn/cute/

echo '<h1>B200' >> /tmp/workspace/fa4_output.txt
nvidia-smi -q -d POWER | grep 'Current Power Limit' | head -1 | cut -d : -f 2 >> /tmp/workspace/fa4_output.txt
echo '</h1>' >> /tmp/workspace/fa4_output.txt
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12 changes: 10 additions & 2 deletions .github/workflows/vllm-benchmark.yml
Original file line number Diff line number Diff line change
Expand Up @@ -327,9 +327,17 @@ jobs:
"${DOCKER_IMAGE}"
)
if [[ "${DEVICE_NAME}" == "cuda" ]]; then
docker exec -t "${container_name}" bash -c "pip install torchao==0.14.1 fbgemm-gpu-genai==1.4.1"
docker exec -t "${container_name}" bash -c "
pip install torchao==0.14.1 fbgemm-gpu-genai==1.4.1

# A quick mitigation for https://github.com/vllm-project/vllm/issues/32373
rm /etc/ld.so.conf.d/00-cuda-compat.conf || true
ldconfig
"
fi
docker exec -t "${container_name}" bash -c "cd vllm-benchmarks/vllm && bash .buildkite/performance-benchmarks/scripts/run-performance-benchmarks.sh"
docker exec -t "${container_name}" bash -c "
cd vllm-benchmarks/vllm && bash .buildkite/performance-benchmarks/scripts/run-performance-benchmarks.sh
"

- name: Authenticate with AWS
# AWS CUDA runners already have access to the bucket via its runner IAM role
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