NVIDIA-SMI因为无法与NVIDIA驱动程序通信而失败

4 回答

• 9

  我通过从BIOS禁用安全启动控制，解决了“我的华硕笔记本电脑与GTX 950m和Ubuntu 18.04无法与NVIDIA驱动程序通信的NVIDIA-SMI失败” .

  回复于 2024-05-17T17:28:07+08:00
• 0

  我在使用K80 GPU的Google Compute Engine中的Ubuntu 16.04（Linux 4.14内核）上遇到了同样的错误 . 我将内核升级到4.14并且问题解决了 . 以下是我将Linux内核从4.13升级到4.14的方法：

  Step 1:
  Check the existing kernel of your Ubuntu Linux:
  
  uname -a
  
  Step 2:
  
  Ubuntu maintains a website for all the versions of kernel that have 
  been released. At the time of this writing, the latest stable release 
  of Ubuntu kernel is 4.15. If you go to this 
  link: http://kernel.ubuntu.com/~kernel-ppa/mainline/v4.15/, you will 
  see several links for download.
  
  Step 3:
  
  Download the appropriate files based on the type of OS you have. For 64 
  bit, I would download the following deb files:
  
  wget http://kernel.ubuntu.com/~kernel-ppa/mainline/v4.15/linux-headers-
  4.15.0-041500_4.15.0-041500.201802011154_all.deb
  wget http://kernel.ubuntu.com/~kernel-ppa/mainline/v4.15/linux-headers-
  4.15.0-041500-generic_4.15.0-041500.201802011154_amd64.deb
  wget http://kernel.ubuntu.com/~kernel-ppa/mainline/v4.15/linux-image-
  4.15.0-041500-generic_4.15.0-041500.201802011154_amd64.deb
  
  Step 4:
  
  Install all the downloaded deb files:
  
  sudo dpkg -i *.deb
  
  Step 5:
  Reboot your machine and check if the kernel has been updated by:
  uname -a
  

  您应该看到您的内核已经升级，并且希望nvidia-smi可以正常工作 .

  回复于 2024-05-17T17:28:07+08:00
• 5

  运行以下命令以获得正确的NVIDIA驱动程序：

  sudo ubuntu-drivers设备

  然后选择右边并运行：

  sudo apt安装

  回复于 2024-05-17T17:28:07+08:00
• 1

  我必须在g2.2xlarge Ubuntu 14.04LTS实例上安装带有Tensorflow的NVIDIA 367.57驱动程序和CUDA 7.5 . 例如NVIDIA显卡的驱动程序，367_367.57.orig.tar

  现在GRID K520 GPU在我训练张量流模型时正在工作：

  ubuntu@ip-10-0-1-70:~$ nvidia-smi
  Sat Apr  1 18:03:32 2017       
  +-----------------------------------------------------------------------------+
  | NVIDIA-SMI 367.57                 Driver Version: 367.57                    |
  |-------------------------------+----------------------+----------------------+
  | GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
  | Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
  |===============================+======================+======================|
  |   0  GRID K520           Off  | 0000:00:03.0     Off |                  N/A |
  | N/A   39C    P8    43W / 125W |   3800MiB /  4036MiB |      0%      Default |
  +-------------------------------+----------------------+----------------------+
  
  +-----------------------------------------------------------------------------+
  | Processes:                                                       GPU Memory |
  |  GPU       PID  Type  Process name                               Usage      |
  |=============================================================================|
  |    0      2254    C   python                                        3798MiB |
  +-----------------------------------------------------------------------------+
  
  ubuntu@ip-10-0-1-70:~/NVIDIA_CUDA-7.0_Samples/1_Utilities/deviceQuery$ ./deviceQuery 
  ./deviceQuery Starting...
  
   CUDA Device Query (Runtime API) version (CUDART static linking)
  
  Detected 1 CUDA Capable device(s)
  
  Device 0: "GRID K520"
    CUDA Driver Version / Runtime Version          8.0 / 7.0
    CUDA Capability Major/Minor version number:    3.0
    Total amount of global memory:                 4036 MBytes (4232052736 bytes)
    ( 8) Multiprocessors, (192) CUDA Cores/MP:     1536 CUDA Cores
    GPU Max Clock rate:                            797 MHz (0.80 GHz)
    Memory Clock rate:                             2500 Mhz
    Memory Bus Width:                              256-bit
    L2 Cache Size:                                 524288 bytes
    Maximum Texture Dimension Size (x,y,z)         1D=(65536), 2D=(65536, 65536), 3D=(4096, 4096, 4096)
    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: 65536
    Warp size:                                     32
    Maximum number of threads per multiprocessor:  2048
    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): (2147483647, 65535, 65535)
    Maximum memory pitch:                          2147483647 bytes
    Texture alignment:                             512 bytes
    Concurrent copy and kernel execution:          Yes with 2 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 / 0 / 3
    Compute Mode:
       < Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
  
  deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 8.0, CUDA Runtime Version = 7.0, NumDevs = 1, Device0 = GRID K520
  Result = PASS
  

  回复于 2024-05-17T17:28:07+08:00