ARG BASE_IMG=pytorch/manylinux2_28-builder ARG CUDA_VERSION=12.9 # Dependency stage: install system deps, CMake, ccache, Python deps (including torch) FROM ${BASE_IMG}:cuda${CUDA_VERSION} AS deps # Overridable build arguments ARG ARCH=x86_64 ARG CUDA_VERSION=12.9 ARG PYTHON_VERSION=3.10 # Manylinux python path tag, e.g. cp310-cp310 / cp312-cp312 ARG PYTHON_TAG=cp310-cp310 ARG CMAKE_VERSION_MAJOR=3.31 ARG CMAKE_VERSION_MINOR=1 # Install ccache 4.12.1 from source for CUDA support (yum provides old 3.7.7) ARG USE_CCACHE=1 ARG CCACHE_VERSION=4.12.1 ARG GITHUB_ARTIFACTORY=github.com ARG PYTORCH_MIRROR=download.pytorch.org ARG PIP_DEFAULT_INDEX=https://pypi.python.org/simple ENV PYTHON_ROOT_PATH=/opt/python/${PYTHON_TAG} ENV PATH=/opt/cmake/bin:${PATH} ENV LD_LIBRARY_PATH=/lib64:${LD_LIBRARY_PATH} ENV NINJA_STATUS="[%f/%t %es] " ENV FLASHINFER_CUDA_ARCH_LIST="8.0 8.9 9.0a 10.0a 12.0a" # CUDA headers path ENV CPLUS_INCLUDE_PATH=/usr/local/cuda/include/cccl${CPLUS_INCLUDE_PATH:+:${CPLUS_INCLUDE_PATH}} ENV C_INCLUDE_PATH=/usr/local/cuda/include/cccl${C_INCLUDE_PATH:+:${C_INCLUDE_PATH}} # Install build dependencies RUN yum install gcc gcc-c++ make wget tar numactl-devel libibverbs -y --nogpgcheck \ && ln -sv /usr/lib64/libibverbs.so.1 /usr/lib64/libibverbs.so \ && yum clean all && rm -rf /var/cache/yum # Install CMake (cached download) RUN --mount=type=cache,id=sgl-kernel-cmake,target=/cmake-downloads \ set -eux; \ CMAKE_TARBALL=cmake-${CMAKE_VERSION_MAJOR}.${CMAKE_VERSION_MINOR}-linux-${ARCH}.tar.gz; \ # Check if CMake is already cached if [ -f /cmake-downloads/${CMAKE_TARBALL} ]; then \ echo "Using cached CMake from /cmake-downloads/${CMAKE_TARBALL}"; \ cp /cmake-downloads/${CMAKE_TARBALL} .; \ else \ CMAKE_TARBALL_URL=https://${GITHUB_ARTIFACTORY}/Kitware/CMake/releases/download/v${CMAKE_VERSION_MAJOR}.${CMAKE_VERSION_MINOR}/${CMAKE_TARBALL}; \ echo "Downloading CMake from: ${CMAKE_TARBALL_URL}"; \ wget --progress=dot ${CMAKE_TARBALL_URL}; \ # Cache the downloaded file cp ${CMAKE_TARBALL} /cmake-downloads/; \ fi; \ tar -xzf ${CMAKE_TARBALL}; \ mv cmake-${CMAKE_VERSION_MAJOR}.${CMAKE_VERSION_MINOR}-linux-${ARCH} /opt/cmake; \ rm -f ${CMAKE_TARBALL}; \ cmake --version # Install ccache RUN if [ "${USE_CCACHE}" = "1" ]; then \ set -eux && \ cd /tmp && \ wget --progress=dot https://${GITHUB_ARTIFACTORY}/ccache/ccache/releases/download/v${CCACHE_VERSION}/ccache-${CCACHE_VERSION}.tar.xz && \ tar -xf ccache-${CCACHE_VERSION}.tar.xz && \ cd ccache-${CCACHE_VERSION} && \ mkdir build && cd build && \ cmake -D CMAKE_BUILD_TYPE=Release -D CMAKE_INSTALL_PREFIX=/usr -D ENABLE_TESTING=OFF -D REDIS_STORAGE_BACKEND=OFF -D HTTP_STORAGE_BACKEND=OFF -D ENABLE_DOCUMENTATION=OFF .. && \ make -j"$(nproc)" && \ make install && \ ccache --version && \ rm -rf /tmp/ccache-${CCACHE_VERSION}*; \ else \ echo "Skipping ccache build (USE_CCACHE=${USE_CCACHE})"; \ fi RUN set -eux; \ if [ "${ARCH}" = "aarch64" ]; then _LIB=sbsa; else _LIB="${ARCH}"; fi; \ mkdir -p /usr/lib/${ARCH}-linux-gnu/; \ ln -sf /usr/local/cuda-${CUDA_VERSION}/targets/${_LIB}-linux/lib/stubs/libcuda.so /usr/lib/${ARCH}-linux-gnu/libcuda.so # Install Python dependencies (torch + build tools) RUN --mount=type=cache,id=sgl-kernel-pip,target=/root/.cache/pip \ set -eux; \ case "${CUDA_VERSION}" in \ 13.0) TORCH_VER=2.9.1; CU_TAG=cu130 ;; \ 12.9) TORCH_VER=2.9.1; CU_TAG=cu128 ;; \ 12.8) TORCH_VER=2.9.1; CU_TAG=cu128 ;; \ *) TORCH_VER=2.9.1; CU_TAG=cu126 ;; \ esac; \ ${PYTHON_ROOT_PATH}/bin/pip install torch==${TORCH_VER} --index-url https://${PYTORCH_MIRROR}/whl/${CU_TAG}; \ ${PYTHON_ROOT_PATH}/bin/pip install ninja setuptools==75.0.0 wheel==0.41.0 numpy uv scikit-build-core --index-url ${PIP_DEFAULT_INDEX} # Build stage: copy source and build wheel FROM deps AS build WORKDIR /sgl-kernel # Only copy sgl-kernel source so code changes only affect later layers COPY . /sgl-kernel/ # Optional: enable CMake/Ninja profiling (pass non-empty via --build-arg ENABLE_*) ARG ENABLE_CMAKE_PROFILE ARG ENABLE_BUILD_PROFILE ARG ARCH=x86_64 ARG USE_CCACHE=1 # Parallelism knobs (override via --build-arg) # BUILD_JOBS: number of parallel compilation units (ninja -j) # NVCC_THREADS: per-compilation-unit NVCC --threads (multi-arch PTXAS) ARG BUILD_JOBS=0 ARG NVCC_THREADS=32 RUN --mount=type=cache,id=sgl-kernel-ccache,target=/ccache \ --mount=type=cache,id=sgl-kernel-pip,target=/root/.cache/pip \ set -eux; \ if [ "${USE_CCACHE}" = "1" ]; then \ export CCACHE_DIR=/ccache; \ export CCACHE_BASEDIR=/sgl-kernel; \ export CCACHE_MAXSIZE=10G; \ export CCACHE_COMPILERCHECK=content; \ export CCACHE_COMPRESS=true; \ export CCACHE_SLOPPINESS=file_macro,time_macros,include_file_mtime,include_file_ctime; \ export CMAKE_C_COMPILER_LAUNCHER=ccache; \ export CMAKE_CXX_COMPILER_LAUNCHER=ccache; \ export CMAKE_CUDA_COMPILER_LAUNCHER=ccache; \ ccache -sV; \ fi; \ # Setting these flags to reduce OOM chance only on ARM if [ "${ARCH}" = "aarch64" ]; then \ export CUDA_NVCC_FLAGS="-Xcudafe --threads=2"; \ export MAKEFLAGS="-j2"; \ export CMAKE_BUILD_PARALLEL_LEVEL=2; \ export NINJAFLAGS="-j2"; \ echo "ARM detected: Using extra conservative settings (2 parallel jobs)"; \ elif [ "${BUILD_JOBS}" -gt 0 ] 2>/dev/null; then \ export CMAKE_BUILD_PARALLEL_LEVEL=${BUILD_JOBS}; \ else \ export CMAKE_BUILD_PARALLEL_LEVEL=$(echo "$(( $(nproc) * 2 / 3 )) 64" | awk '{print ($1 < $2) ? $1 : $2}'); \ fi; \ export CMAKE_ARGS="${CMAKE_ARGS:-} -DSGL_KERNEL_COMPILE_THREADS=${NVCC_THREADS}"; \ if [ -n "${ENABLE_CMAKE_PROFILE:-}" ]; then \ echo "CMake profiling enabled - will save to /sgl-kernel/cmake-profile.json"; \ export CMAKE_ARGS="${CMAKE_ARGS} --profiling-output=/sgl-kernel/cmake-profile.json --profiling-format=google-trace"; \ fi; \ echo "Build parallelism: CMAKE_BUILD_PARALLEL_LEVEL=${CMAKE_BUILD_PARALLEL_LEVEL}, NVCC_THREADS=${NVCC_THREADS}"; \ echo "CMAKE_ARGS=${CMAKE_ARGS}"; \ ${PYTHON_ROOT_PATH}/bin/python -m uv build --wheel -Cbuild-dir=build . --color=always --no-build-isolation; \ ./rename_wheels.sh; \ if [ -n "${ENABLE_BUILD_PROFILE:-}" ] && [ -f /sgl-kernel/build/.ninja_log ]; then \ echo "Ninja build profiling enabled - will save to /sgl-kernel/build-trace.json"; \ wget --progress=dot https://raw.githubusercontent.com/cradleapps/ninjatracing/084212eaf68f25c70579958a2ed67fb4ec2a9ca4/ninjatracing -O /tmp/ninjatracing; \ if [ -f /tmp/ninjatracing ]; then \ ${PYTHON_ROOT_PATH}/bin/python /tmp/ninjatracing /sgl-kernel/build/.ninja_log > /sgl-kernel/build-trace.json; \ fi; \ if [ -f /sgl-kernel/build-trace.json ]; then \ gzip -9 -k /sgl-kernel/build-trace.json 2>/dev/null || true; \ echo "Build trace saved to: build-trace.json"; \ if [ -f /sgl-kernel/build-trace.json.gz ]; then \ ORIGINAL_SIZE=$(stat -f%z /sgl-kernel/build-trace.json 2>/dev/null || stat -c%s /sgl-kernel/build-trace.json); \ COMPRESSED_SIZE=$(stat -f%z /sgl-kernel/build-trace.json.gz 2>/dev/null || stat -c%s /sgl-kernel/build-trace.json.gz); \ RATIO=$(( (ORIGINAL_SIZE - COMPRESSED_SIZE) * 100 / ORIGINAL_SIZE )); \ echo "Compressed to: build-trace.json.gz (${RATIO}% smaller)"; \ fi; \ echo ""; \ echo "View in browser:"; \ echo " - chrome://tracing (load JSON file)"; \ echo " - ui.perfetto.dev (recommended, supports .gz files)"; \ echo ""; \ echo "Shows:"; \ echo " - Compilation time per file"; \ echo " - Parallelism utilization"; \ echo " - Critical path (longest dependency chain)"; \ echo " - Where the 2-hour build time went"; \ fi; \ fi; \ if [ "${USE_CCACHE}" = "1" ]; then \ echo "ccache Statistics"; \ ccache -s; \ else \ echo "ccache disabled (USE_CCACHE=${USE_CCACHE})"; \ fi # Artifact stage (for --output to export wheel) FROM scratch AS artifact COPY --from=build /sgl-kernel/dist/*.whl /