Ubuntu18.04+RTX3070+driver460.67 在base安装cuda11.2

Ubuntu18.04+RTX3070+driver460.67

在base安装cuda11.2

1. 首先找GPU对应的cuda版本。

   1. 查询本机的驱动版本：

      ​ nvidia-smi
      ​ nvidia-smi -a

   2. 查询本机驱动对应的cuda版本：

      https://docs.nvidia.com/cuda/cuda-toolkit-release-notes/index.html
      

2. 下载对应的cuda，由于我的系统已经安装驱动且使用.run文件会报driver not selection的错误，debug太麻烦，参考社区的讨论.我选择下载network版的deb文件安装。

   其中替换最后一步的cuda为cuda-toolkit-11-2。具体的每一步为：

   wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-ubuntu1804.pin
   sudo mv cuda-ubuntu1804.pin /etc/apt/preferences.d/cuda-repository-pin-600
   sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub
   sudo add-apt-repository "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/ /"
   sudo apt-get update
   sudo apt-get -y install cuda-toolkit-11-2
   

3. 设置环境变量

   1. 插曲：安装vim sudo apt-get install vim

   2. sudo vim ~/.bashrc

      输入a开始修改

      在文件最后添加：

export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda-11.2/lib64
export PATH=$PATH:/usr/local/cuda-11.2/bin
export CUDA_HOME=$CUDA_HOME:/usr/local/cuda-11.2
     

保存退出

3. source ~/.bashrc

4. sudo vim /etc/profile

   添加：export PATH=/usr/local/cuda/bin:$PATH

5. sudo vim /etc/ld.so.conf.d/cuda.conf

   1. 添加：/usr/local/cuda/lib64
   2. 退出后： sudo ldconfig

6. 测试是否安装成功。

 cd NVIDIA_CUDA-11.2_Samples
 sudo make all -j4
cd bin/x86_64/linux/release
 ./deviceQuery

2. 如果成功，会出现…+pass

      $ ./deviceQuery
      ./deviceQuery Starting...
      
       CUDA Device Query (Runtime API) version (CUDART static linking)
      
      Detected 1 CUDA Capable device(s)
      
      Device 0: "GeForce GT 635M"
        CUDA Driver Version / Runtime Version          9.0 / 8.0
        CUDA Capability Major/Minor version number:    2.1
        Total amount of global memory:                 1985 MBytes (2081619968 bytes)
        ( 2) Multiprocessors, ( 48) CUDA Cores/MP:     96 CUDA Cores
        GPU Max Clock rate:                            950 MHz (0.95 GHz)
        Memory Clock rate:                             900 Mhz
        Memory Bus Width:                              128-bit
        L2 Cache Size:                                 131072 bytes
        Maximum Texture Dimension Size (x,y,z)         1D=(65536), 2D=(65536, 65535), 3D=(2048, 2048, 2048)
        Maximum Layered 1D Texture Size, (num) layers  1D=(16384), 2048 layers
        Maximum Layered 2D Texture Size, (num) layers  2D=(16384, 16384), 2048 layers
        Total amount of constant memory:               65536 bytes
        Total amount of shared memory per block:       49152 bytes
        Total number of registers available per block: 32768
        Warp size:                                     32
        Maximum number of threads per multiprocessor:  1536
        Maximum number of threads per block:           1024
        Max dimension size of a thread block (x,y,z): (1024, 1024, 64)
        Max dimension size of a grid size    (x,y,z): (65535, 65535, 65535)
        Maximum memory pitch:                          2147483647 bytes
        Texture alignment:                             512 bytes
        Concurrent copy and kernel execution:          Yes with 1 copy engine(s)
        Run time limit on kernels:                     No
        Integrated GPU sharing Host Memory:            No
        Support host page-locked memory mapping:       Yes
        Alignment requirement for Surfaces:            Yes
        Device has ECC support:                        Disabled
        Device supports Unified Addressing (UVA):      Yes
        Device PCI Domain ID / Bus ID / location ID:   0 / 1 / 0
        Compute Mode:
           < Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
      
      deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 9.0, CUDA Runtime Version = 8.0, NumDevs = 1, Device0 = GeForce GT 635M
      Result = PASS
   

测试是否安装成功方法二：

   nvcc -V

若成功：

reference：

1. https://zhuanlan.zhihu.com/p/79059379
2. https://blog.youkuaiyun.com/wf19930209/article/details/81879514
3. https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html
4. https://blog.youkuaiyun.com/s_sunnyy/article/details/64121826
5. https://zhuanlan.zhihu.com/p/122286055
6. https://www.cnblogs.com/tinywan/p/7230039.html
7. https://www.jianshu.com/p/09ef0ad2ef4a
8. https://blog.youkuaiyun.com/weixin_42513534/article/details/114922851
9. https://blog.youkuaiyun.com/xinxi009gyx/article/details/80994948
10. https://zhuanlan.zhihu.com/p/72298520
11. https://zhuanlan.zhihu.com/p/136371009
12. https://www.jianshu.com/p/4e8a4a07cc57
13. https://www.jianshu.com/p/00c37b09f0f3
14. https://forums.developer.nvidia.com/t/rtx-3070-with-cuda10-0-compatibility-ubuntuos-any-version/168904/2
15. https://developer.nvidia.com/cuda-downloads?target_os=Linux&target_arch=x86_64&target_distro=Ubuntu&target_version=1804&target_type=deblocal