xgboost 多gpu支持 编译
Ubuntu 18.04.2
Linux 4.15.0-46-generic
gcc (Ubuntu 7.3.0-27ubuntu1~18.04) 7.3.0
cuda 10.0
https://docs.nvidia.com/cuda/archive/10.0/cuda-installation-guide-linux/index.html#verify-you-have-supported-version-of-linux
安装略
nccl2
git clone https://github.com/NVIDIA/nccl.git
cd nccl
make -j src.build
xgboost
(建议选择稳定版源码编译 如 0.82)
mkdir xgboost-src
git clone --recursive https://github.com/dmlc/xgboost.git
或
git clone https://github.com/dmlc/xgboost.git
git submodule init
git submodule update
设置版本0.82(!然而最后安装后的版本是0.81)
git checkout 3f83dcd
mkdir build
cd build
cmake .. -DUSE_CUDA=ON -DUSE_NCCL=ON -DNCCL_ROOT=/xxx/install/nccl-src/nccl/build
make -j4
直至出现类似结果
...
Scanning dependencies of target gpuxgboost
[ 95%] Linking CXX static library libgpuxgboost.a
[ 95%] Built target gpuxgboost
Scanning dependencies of target runxgboost
[ 97%] Building CXX object CMakeFiles/runxgboost.dir/src/cli_main.cc.o
[ 98%] Linking CXX executable ../xgboost
[ 98%] Built target runxgboost
Scanning dependencies of target xgboost
[100%] Linking CXX shared library ../lib/libxgboost.so
[100%] Built target xgboost
cd ../python-package
python setup.py install
备注: 如果切换 使用 update-alternatives gcc/g++ 版本时，可能会出现各种引用异常，此时建议切换到gcc/g++某个已安装版本(如7.3)， 重启机器
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tensorflow (对应cuda 10.0)
tensorflow-gpu 1.13.1
pip install tensorflow-gpu
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torch (对应cuda 10.0)
pip install https://download.pytorch.org/whl/cu100/torch-1.0.1.post2-cp36-cp36m-linux_x86_64.whl
pip install torchvision
