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Add Windows CUDA llama.cpp release asset

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Adds a Windows x64 CUDA release asset for the llama.cpp SenseVoice runtime, with CUDA Toolkit setup, architecture-86 build flags, focused SenseVoice target packaging, docs, and workflow regression tests. Manual workflow dispatch 29656771776 passed all build matrix jobs including build-windows-x64-cuda.
This commit is contained in:
zhifu gao
2026-07-19 03:24:07 +08:00
committed by GitHub
parent 57721fc8ce
commit f1e287edc2
4 changed files with 109 additions and 7 deletions
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.github/workflows/build-llamacpp-binaries.yml
+53 -3
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@@ -82,13 +82,48 @@ jobs:
-DGGML_FMA=ON
-DGGML_F16C=ON
-DGGML_BMI2=ON
- os: windows-latest
name: windows-x64-cuda
cuda: true
cuda_version: '13.2.0'
cuda_architectures: '86'
build_target: llama-funasr-sensevoice
timeout_minutes: 90
cmake_flags: >-
-DGGML_NATIVE=OFF
-DGGML_CUDA=ON
-DGGML_CUDA_FORCE_CUBLAS=ON
-DGGML_CUDA_FA=OFF
-DGGML_CUDA_NCCL=OFF
-DGGML_CUDA_GRAPHS=OFF
-DGGML_AVX=OFF
-DGGML_AVX2=OFF
-DGGML_AVX_VNNI=OFF
-DGGML_AVX512=OFF
-DGGML_AVX512_VBMI=OFF
-DGGML_AVX512_VNNI=OFF
-DGGML_AVX512_BF16=OFF
-DGGML_FMA=OFF
-DGGML_F16C=OFF
-DGGML_BMI2=OFF
runs-on: ${{ matrix.os }}
timeout-minutes: ${{ matrix.timeout_minutes || 30 }}
defaults:
run:
shell: bash
working-directory: runtime/llama.cpp
steps:
- uses: actions/checkout@v4
- name: Install CUDA Toolkit
if: matrix.cuda
uses: Jimver/[email protected]
with:
cuda: ${{ matrix.cuda_version }}
method: network
log-file-suffix: ${{ matrix.name }}.txt
- name: Show CUDA compiler
if: matrix.cuda
run: nvcc --version
- name: Configure and build
run: |
# Release binaries must be portable across user machines, not tuned to
@@ -96,8 +131,23 @@ jobs:
# AVX-VNNI instructions and then crash with SIGILL on ordinary CPUs.
# Keep the default x64 package conservative, and publish explicit
# x64-avx2 assets for machines that support AVX2/FMA/F16C/BMI2.
cmake -B build -DCMAKE_BUILD_TYPE=Release ${{ matrix.cmake_flags }}
cmake --build build --config Release -j 2
# The CUDA release asset is SenseVoiceSmall-specific for now; building
# only that target keeps the Windows CUDA job bounded and matches the
# backend currently exposed by `--backend cuda`.
cmake_args=(
-B build
-DCMAKE_BUILD_TYPE=Release
${{ matrix.cmake_flags }}
)
if [ -n "${{ matrix.cuda_architectures }}" ]; then
cmake_args+=("-DCMAKE_CUDA_ARCHITECTURES=${{ matrix.cuda_architectures }}")
fi
cmake "${cmake_args[@]}"
if [ -n "${{ matrix.build_target }}" ]; then
cmake --build build --config Release -j 2 --target "${{ matrix.build_target }}"
else
cmake --build build --config Release -j 2
fi
- name: Package
run: |
mkdir -p pkg
@@ -135,4 +185,4 @@ jobs:
gh release create "$tag" dist/* \
--repo "${{ github.repository }}" \
--title "FunASR llama.cpp runtime $version" \
--notes "Prebuilt self-contained binaries for the FunASR llama.cpp / GGUF runtime: SenseVoice, Paraformer and Fun-ASR-Nano with built-in FSMN-VAD. Download the default quantized model with \`bash download-funasr-model.sh <sensevoice|paraformer|nano>\` (the helper requires the Hugging Face CLI: \`pip install -U huggingface_hub\`), then run \`llama-funasr-cli\` / \`llama-funasr-sensevoice\` / \`llama-funasr-paraformer\`. Use the default x64 asset for maximum CPU compatibility; use the x64-avx2 asset on CPUs with AVX2/FMA/F16C/BMI2 for higher throughput. No Python ASR runtime or local build is required. Docs: $docs"
--notes "Prebuilt self-contained binaries for the FunASR llama.cpp / GGUF runtime: SenseVoice, Paraformer and Fun-ASR-Nano with built-in FSMN-VAD. Download the default quantized model with \`bash download-funasr-model.sh <sensevoice|paraformer|nano>\` (the helper requires the Hugging Face CLI: \`pip install -U huggingface_hub\`), then run \`llama-funasr-cli\` / \`llama-funasr-sensevoice\` / \`llama-funasr-paraformer\`. Use the default x64 asset for maximum CPU compatibility; use the x64-avx2 asset on CPUs with AVX2/FMA/F16C/BMI2 for higher throughput. The Windows CUDA asset is \`windows-x64-cuda\`; it requires an NVIDIA driver compatible with the CUDA Toolkit version configured by the release workflow, targets CUDA architecture 86, and enables SenseVoiceSmall graph execution with \`llama-funasr-sensevoice ... --backend cuda\`. Build from source for other GPU architectures. No Python ASR runtime or local build is required. Docs: $docs"
runtime/llama.cpp/CMakeLists.txt
+8 -1
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@@ -24,6 +24,9 @@ if(NOT CMAKE_BUILD_TYPE AND NOT CMAKE_CONFIGURATION_TYPES)
endif()
include(FetchContent)
if(POLICY CMP0169)
cmake_policy(SET CMP0169 OLD)
endif()
set(LLAMA_BUILD_TESTS OFF CACHE BOOL "" FORCE)
set(LLAMA_BUILD_EXAMPLES OFF CACHE BOOL "" FORCE)
set(LLAMA_BUILD_TOOLS OFF CACHE BOOL "" FORCE)
@@ -32,7 +35,11 @@ set(LLAMA_CURL OFF CACHE BOOL "" FORCE)
FetchContent_Declare(llama
GIT_REPOSITORY https://github.com/ggml-org/llama.cpp.git
GIT_TAG 8086439a4cea94c71a5dfb8fe4ad1546aebd640f)
FetchContent_MakeAvailable(llama)
FetchContent_GetProperties(llama)
if(NOT llama_POPULATED)
FetchContent_Populate(llama)
add_subdirectory(${llama_SOURCE_DIR} ${llama_BINARY_DIR})
endif()
find_package(Threads REQUIRED)
set(FUNASR_COMMON ${CMAKE_CURRENT_SOURCE_DIR}/funasr-common)
runtime/llama.cpp/README.md
+7 -3
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@@ -72,9 +72,13 @@ cmake --build build-cuda -j --target llama-funasr-sensevoice
-m sensevoice-small-f16.gguf -a sample.wav --backend cuda
```
`--backend cpu` remains the default and is what the current cross-platform
prebuilt binaries use. A binary built without `-DGGML_CUDA=ON` exits with a clear
message if `--backend cuda` is requested.
`--backend cpu` remains the default and is what the portable cross-platform
prebuilt binaries use. Tagged runtime releases also publish a
`funasr-llamacpp-windows-x64-cuda.zip` package when the Windows CUDA release job
passes; it requires an NVIDIA driver compatible with the CUDA Toolkit version
configured by that release job and targets CUDA architecture 86. Build from source
for other GPU architectures. A binary built without `-DGGML_CUDA=ON` exits with a
clear message if `--backend cuda` is requested.
## Build (shared)
```bash
runtime/llama.cpp/tests/test_release_workflow.py
+41
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@@ -0,0 +1,41 @@
from pathlib import Path
ROOT = Path(__file__).resolve().parents[3]
WORKFLOW = ROOT / ".github" / "workflows" / "build-llamacpp-binaries.yml"
def test_windows_cuda_release_asset_is_in_matrix():
workflow = WORKFLOW.read_text(encoding="utf-8")
assert "name: windows-x64-cuda" in workflow
assert "cuda: true" in workflow
assert "windows-x64-cuda" in workflow
assert "cuda_architectures: '86'" in workflow
assert "build_target: llama-funasr-sensevoice" in workflow
assert "timeout_minutes: 90" in workflow
def test_windows_cuda_build_uses_cuda_toolkit_and_flags():
workflow = WORKFLOW.read_text(encoding="utf-8")
assert "Jimver/cuda-toolkit" in workflow
assert "if: matrix.cuda" in workflow
assert "-DGGML_CUDA=ON" in workflow
assert "-DGGML_CUDA_FORCE_CUBLAS=ON" in workflow
assert "-DGGML_CUDA_FA=OFF" in workflow
assert "-DGGML_CUDA_NCCL=OFF" in workflow
assert "CMAKE_CUDA_ARCHITECTURES=${{ matrix.cuda_architectures }}" in workflow
assert "cmake \"${cmake_args[@]}\"" in workflow
assert "--target \"${{ matrix.build_target }}\"" in workflow
def test_release_notes_explain_cpu_and_cuda_windows_assets():
readme = (ROOT / "runtime" / "llama.cpp" / "README.md").read_text(encoding="utf-8")
assert "windows-x64-cuda" in readme
assert "--backend cuda" in readme
assert "Windows CUDA" in readme
assert "CUDA architecture 86" in readme
assert "Build from source" in readme
assert "other GPU architectures" in readme