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musa: upgrade musa sdk to rc4.2.0 #14498
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esrakorkmz
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Signed-off-by: Xiaodong Ye <[email protected]>
Signed-off-by: Xiaodong Ye <[email protected]>
Signed-off-by: Xiaodong Ye <[email protected]>
Signed-off-by: Xiaodong Ye <[email protected]>
Signed-off-by: Xiaodong Ye <[email protected]>
Signed-off-by: Xiaodong Ye <[email protected]>
Signed-off-by: Xiaodong Ye <[email protected]>
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This was referenced Jul 24, 2025
ggerganov
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Labels
devops
improvements to build systems and github actions
documentation
Improvements or additions to documentation
ggml
changes relating to the ggml tensor library for machine learning
Nvidia GPU
Issues specific to Nvidia GPUs
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Make sure to read the contributing guidelines before submitting a PR
This PR upgrades the MUSA SDK from
rc4.0.1
torc4.2.0
.Key updates
rc4.2.0
and switch back to non-muDNN variantGGML_MUSA_GRAPHS
for enabling MUSA graphs andGGML_MUSA_MUDNN_COPY
for enabling muDNN copy accelerationWhy disable muDNN by default
Although enabling muDNN can accelerate contiguous device memory copies, MUSA SDK
rc4.2.0
no longer includes the fat binary and instead provides per-architecture binaries. Additionally, the performance ofmusaMemcpyAsync
has been improved in this release, making the performance gap minimal.Testing Done
test-backend-ops
passed.All Docker builds passed.
Verified the server image works as expected.
docker run -p 8080:8080 -it -v ~/models:/models local/llama.cpp:server-musa -m /models/DeepSeek-R1-Distill-Qwen-7B-Q4_K_M.gguf -ngl 999
Local build with
-DGGML_MUSA_GRAPHS=ON
succeeded.root@7bd6a1e5dcc0:/ws# cmake -B build -DGGML_MUSA=ON -DMUSA_ARCHITECTURES=21 -DGGML_MUSA_GRAPHS=ON root@7bd6a1e5dcc0:/ws# cmake --build build -j $(nproc) --config Release
Local build with
-DGGML_MUSA_MUDNN_COPY=ON
also succeeded when using the muDNN Docker image (as expected, it would fail with the non-muDNN variant).root@7bd6a1e5dcc0:/ws# cmake -B build -DGGML_MUSA=ON -DMUSA_ARCHITECTURES=21 -DGGML_MUSA_MUDNN_COPY=ON root@7bd6a1e5dcc0:/ws# cmake --build build -j $(nproc) --config Release