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 ------------------------------------------------------ tensorflow (对应cuda 10.0)      tensorflow-gpu        1.13.1      pip install tensorflow-gpu ------------------------------------------------------ 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