Wei Peng

淡泊明志,宁静致远

Using the blog to record the daily progress.


welcome to bowenroom

gluon&mxnet的gpu环境搭建

  1. 首先来更新一下sudo apt-get update
  2. sudo apt-get install build-essential git
  3. wget https://developer.nvidia.com/compute/cuda/8.0/Prod2/local_installers/cuda_8.0.61_375.26_linux-run (获取cuda的地址)
  4. chmod +x cuda_8.0.61_375.26_linux-run(获取权限)
  5. 服务器端安装比较简单,推荐使用google cloud,还有一段时间免费的gpu可以使用….
  6. 本地安装一般会出现图形界面的问题,服务器则不会
    7.
    sudo /etc/init.d/lightdm stop
    sudo /etc/init.d/lightdm status
    # 别忘了搞定后重新打开
    sudo /etc/init.d/lightdm restart
    
  7. sudo ./cuda_8.0.61_375.26_linux-run 按照步骤一步步安装驱动
  8. nvidia-smi看一下是否安装好nvidia驱动
  9. 安装anaconda wget https://repo.continuum.io/archive/Anaconda3-5.0.1-Linux-x86_64.sh
  10. bash Anaconda

    补充:最好设置git走代理

  11. Missing dependencies for SOCKS support.的错误:pip install requests[socks]

    或者是

    Unset socks proxy, in your case: 
    unset all_proxy
    unset ALL_PROXY
    Install missing dependencies: 
    pip install pysocks
    Reset proxy, source .bashrc, and pip install works again with socks proxy.
    
  12. 需要在bashrc中配置的内容(jp只是自己设置的简化指令,省的每次敲一大堆..):
    export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda-8.0/lib64
    export PATH=/home/bowenroom/miniconda3/bin:$PATH
    alias gluon='source activate gluon'
    alias jp='MXNET_GLUON_REPO=https://apache-mxnet.s3.cn-north-1.amazonaws.com.cn/ jupyter notebook --NotebookApp.contents_manager_class='notedown.NotedownContentsManager'
    '
    
  13. 关于numpy的操作不支持gpu,所有使用到numpy的地方,都是用的cpu
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