forked from Karylab-cklius/vllm
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07782ff2fc | ||
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0295b4555c | ||
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702e82e422 |
@@ -8,6 +8,21 @@ steps:
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- group: "Build Python wheels"
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key: "build-wheels"
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steps:
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- label: "Build wheel - aarch64 - CUDA 12.8"
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depends_on: ~
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id: build-wheel-arm64-cuda-12-8
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agents:
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queue: arm64_cpu_queue_postmerge
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commands:
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# #NOTE: torch_cuda_arch_list is derived from upstream PyTorch build files here:
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# https://github.com/pytorch/pytorch/blob/main/.ci/aarch64_linux/aarch64_ci_build.sh#L7
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- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg USE_SCCACHE=1 --build-arg GIT_REPO_CHECK=1 --build-arg CUDA_VERSION=12.8.1 --build-arg torch_cuda_arch_list='8.7 8.9 9.0 10.0+PTX' --tag vllm-ci:build-image --target build --progress plain -f docker/Dockerfile ."
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- "mkdir artifacts"
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- "docker run --rm -v $(pwd)/artifacts:/artifacts_host vllm-ci:build-image bash -c 'cp -r dist /artifacts_host && chmod -R a+rw /artifacts_host'"
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- "bash .buildkite/scripts/upload-nightly-wheels.sh"
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env:
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DOCKER_BUILDKIT: "1"
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- label: "Build wheel - aarch64 - CUDA 12.9"
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depends_on: ~
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id: build-wheel-arm64-cuda-12-9
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@@ -51,6 +66,19 @@ steps:
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env:
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DOCKER_BUILDKIT: "1"
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- label: "Build wheel - x86_64 - CUDA 12.8"
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depends_on: ~
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id: build-wheel-x86-cuda-12-8
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agents:
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queue: cpu_queue_postmerge
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commands:
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- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg USE_SCCACHE=1 --build-arg GIT_REPO_CHECK=1 --build-arg CUDA_VERSION=12.8.1 --tag vllm-ci:build-image --target build --progress plain -f docker/Dockerfile ."
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- "mkdir artifacts"
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- "docker run --rm -v $(pwd)/artifacts:/artifacts_host vllm-ci:build-image bash -c 'cp -r dist /artifacts_host && chmod -R a+rw /artifacts_host'"
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- "bash .buildkite/scripts/upload-nightly-wheels.sh manylinux_2_31"
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env:
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DOCKER_BUILDKIT: "1"
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- label: "Build wheel - x86_64 - CUDA 12.9"
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depends_on: ~
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id: build-wheel-x86-cuda-12-9
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@@ -19,7 +19,7 @@ else()
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FetchContent_Declare(
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flashmla
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GIT_REPOSITORY https://github.com/vllm-project/FlashMLA
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GIT_TAG 692917b1cda61b93ac9ee2d846ec54e75afe87b1
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GIT_TAG f46984b4caf19409bf4ab94a540341918dd6a1a3
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GIT_PROGRESS TRUE
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CONFIGURE_COMMAND ""
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BUILD_COMMAND ""
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@@ -13,8 +13,13 @@ struct alignas(32) u32x8_t {
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uint32_t u0, u1, u2, u3, u4, u5, u6, u7;
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};
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// 256-bit vector loads require both sm_100+ and CUDA 12.9+
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#define VLLM_SUPPORTS_256BIT_VECTORS \
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(defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 1000 && \
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__CUDACC_VER_MAJOR__ >= 12 && __CUDACC_VER_MINOR__ >= 9)
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__device__ __forceinline__ void ld256(u32x8_t& val, const u32x8_t* ptr) {
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#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 1000
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#if VLLM_SUPPORTS_256BIT_VECTORS
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asm volatile("ld.global.nc.v8.u32 {%0,%1,%2,%3,%4,%5,%6,%7}, [%8];\n"
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: "=r"(val.u0), "=r"(val.u1), "=r"(val.u2), "=r"(val.u3),
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"=r"(val.u4), "=r"(val.u5), "=r"(val.u6), "=r"(val.u7)
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@@ -35,7 +40,7 @@ __device__ __forceinline__ void ld256(u32x8_t& val, const u32x8_t* ptr) {
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}
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__device__ __forceinline__ void st256(u32x8_t& val, u32x8_t* ptr) {
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#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 1000
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#if VLLM_SUPPORTS_256BIT_VECTORS
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asm volatile("st.global.v8.u32 [%0], {%1,%2,%3,%4,%5,%6,%7,%8};\n"
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:
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: "l"(ptr), "r"(val.u0), "r"(val.u1), "r"(val.u2), "r"(val.u3),
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+4
-8
@@ -418,10 +418,6 @@ RUN --mount=type=cache,target=/root/.cache/uv \
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fi && \
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python3 setup.py bdist_wheel --dist-dir=dist --py-limited-api=cp38
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# Copy extension wheels from extensions-build stage for later use
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COPY --from=extensions-build /tmp/deepgemm/dist /tmp/deepgemm/dist
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COPY --from=extensions-build /tmp/ep_kernels_workspace/dist /tmp/ep_kernels_workspace/dist
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# Check the size of the wheel if RUN_WHEEL_CHECK is true
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COPY .buildkite/check-wheel-size.py check-wheel-size.py
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# sync the default value with .buildkite/check-wheel-size.py
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@@ -660,9 +656,9 @@ RUN --mount=type=cache,target=/root/.cache/uv \
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. /etc/environment && \
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uv pip list
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# Install deepgemm wheel that has been built in the `build` stage
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# Install deepgemm wheel that has been built in the `extensions-build` stage
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RUN --mount=type=cache,target=/root/.cache/uv \
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--mount=type=bind,from=build,source=/tmp/deepgemm/dist,target=/tmp/deepgemm/dist,ro \
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--mount=type=bind,from=extensions-build,source=/tmp/deepgemm/dist,target=/tmp/deepgemm/dist,ro \
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sh -c 'if ls /tmp/deepgemm/dist/*.whl >/dev/null 2>&1; then \
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uv pip install --system /tmp/deepgemm/dist/*.whl; \
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else \
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@@ -672,8 +668,8 @@ RUN --mount=type=cache,target=/root/.cache/uv \
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# Pytorch now installs NVSHMEM, setting LD_LIBRARY_PATH
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ENV LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH
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# Install EP kernels wheels (pplx-kernels and DeepEP) that have been built in the `build` stage
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RUN --mount=type=bind,from=build,src=/tmp/ep_kernels_workspace/dist,target=/vllm-workspace/ep_kernels/dist \
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# Install EP kernels wheels (pplx-kernels and DeepEP) that have been built in the `extensions-build` stage
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RUN --mount=type=bind,from=extensions-build,src=/tmp/ep_kernels_workspace/dist,target=/vllm-workspace/ep_kernels/dist \
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--mount=type=cache,target=/root/.cache/uv \
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uv pip install --system ep_kernels/dist/*.whl --verbose \
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--extra-index-url ${PYTORCH_CUDA_INDEX_BASE_URL}/cu$(echo $CUDA_VERSION | cut -d. -f1,2 | tr -d '.')
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Binary file not shown.
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Before Width: | Height: | Size: 325 KiB After Width: | Height: | Size: 331 KiB |
@@ -977,9 +977,9 @@ if _is_cuda():
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# FA3 requires CUDA 12.3 or later
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ext_modules.append(CMakeExtension(name="vllm.vllm_flash_attn._vllm_fa3_C"))
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if envs.VLLM_USE_PRECOMPILED or (
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CUDA_HOME and get_nvcc_cuda_version() >= Version("12.9")
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CUDA_HOME and get_nvcc_cuda_version() >= Version("12.8")
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):
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# FlashMLA requires CUDA 12.9 or later
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# FlashMLA requires CUDA 12.8 or later
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# Optional since this doesn't get built (produce an .so file) when
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# not targeting a hopper system
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ext_modules.append(CMakeExtension(name="vllm._flashmla_C", optional=True))
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