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[CI] Prune unused archs from libnccl (#8179)

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* [CI] Prune unused archs from libnccl

* Put pruning logic in CI directory

* Don't use --color in grep
This commit is contained in:
Philip Hyunsu Cho 2022-08-21 01:46:16 -07:00 committed by GitHub
parent ad3bc0edee
commit 35ef8abc27
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GPG Key ID: 4AEE18F83AFDEB23
3 changed files with 42 additions and 8 deletions
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9
Jenkinsfile vendored
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@ -114,10 +114,6 @@ def checkoutSrcs() {
}
}
def GetCUDABuildContainerType(cuda_version) {
return (cuda_version == ref_cuda_ver) ? 'gpu_build_centos7' : 'gpu_build'
}
def ClangTidy() {
node('linux && cpu_build') {
unstash name: 'srcs'
@ -208,7 +204,7 @@ def BuildCUDA(args) {
node('linux && cpu_build') {
unstash name: 'srcs'
echo "Build with CUDA ${args.cuda_version}"
def container_type = GetCUDABuildContainerType(args.cuda_version)
def container_type = "gpu_build_centos7"
def docker_binary = "docker"
def docker_args = "--build-arg CUDA_VERSION_ARG=${args.cuda_version}"
def arch_flag = ""
@ -217,7 +213,8 @@ def BuildCUDA(args) {
}
def wheel_tag = "manylinux2014_x86_64"
sh """
${dockerRun} ${container_type} ${docker_binary} ${docker_args} tests/ci_build/build_via_cmake.sh -DUSE_CUDA=ON -DUSE_NCCL=ON -DOPEN_MP:BOOL=ON -DHIDE_CXX_SYMBOLS=ON ${arch_flag}
${dockerRun} ${container_type} ${docker_binary} ${docker_args} tests/ci_build/prune_libnccl.sh
${dockerRun} ${container_type} ${docker_binary} ${docker_args} tests/ci_build/build_via_cmake.sh -DUSE_CUDA=ON -DUSE_NCCL=ON -DUSE_OPENMP=ON -DHIDE_CXX_SYMBOLS=ON -DUSE_NCCL_LIB_PATH=ON -DNCCL_INCLUDE_DIR=/usr/include -DNCCL_LIBRARY=/workspace/libnccl_static.a ${arch_flag}
${dockerRun} ${container_type} ${docker_binary} ${docker_args} bash -c "cd python-package && rm -rf dist/* && python setup.py bdist_wheel --universal"
${dockerRun} ${container_type} ${docker_binary} ${docker_args} python tests/ci_build/rename_whl.py python-package/dist/*.whl ${commit_id} ${wheel_tag}
"""

4
tests/ci_build/Dockerfile.gpu_build_centos7
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@ -15,8 +15,8 @@ RUN \
bash Miniconda3.sh -b -p /opt/python && \
/opt/python/bin/python -m pip install awscli && \
# CMake
wget -nv -nc https://cmake.org/files/v3.14/cmake-3.14.0-Linux-x86_64.sh --no-check-certificate && \
bash cmake-3.14.0-Linux-x86_64.sh --skip-license --prefix=/usr
wget -nv -nc https://cmake.org/files/v3.18/cmake-3.18.0-Linux-x86_64.sh --no-check-certificate && \
bash cmake-3.18.0-Linux-x86_64.sh --skip-license --prefix=/usr
# NCCL2 (License: https://docs.nvidia.com/deeplearning/sdk/nccl-sla/index.html)
RUN \

37
tests/ci_build/prune_libnccl.sh Executable file
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@ -0,0 +1,37 @@
#!/usr/bin/env bash
set -e
rm -rf tmp_nccl
mkdir tmp_nccl
pushd tmp_nccl
set -x
cat << EOF > test.cu
int main(void) { return 0; }
EOF
cat << EOF > CMakeLists.txt
cmake_minimum_required(VERSION 3.18 FATAL_ERROR)
project(gencode_extractor CXX C)
cmake_policy(SET CMP0104 NEW)
set(CMAKE_CUDA_HOST_COMPILER \${CMAKE_CXX_COMPILER})
enable_language(CUDA)
include(../cmake/Utils.cmake)
set(GEN_CODE "")
format_gencode_flags("" GEN_CODE)
add_library(test OBJECT test.cu)
set_property(TARGET test PROPERTY CUDA_ARCHITECTURES \${CMAKE_CUDA_ARCHITECTURES})
set(CMAKE_EXPORT_COMPILE_COMMANDS ON)
EOF
cmake . -GNinja
gen_code=$(grep -o -- '--generate-code=\S*' compile_commands.json | paste -sd ' ')
nvprune ${gen_code} /usr/lib64/libnccl_static.a -o ../libnccl_static.a
popd
rm -rf tmp_nccl
set +x