如何安装 NVIDA 工具包(使用包管理器,无法提供 .deb 文件名)

如何安装 NVIDA 工具包(使用包管理器,无法提供 .deb 文件名)

我使用的是 Ubuntu 14.04 LTS,几个月来一直在使用 NVIDIA 和 CUDA。今天早上,在 ubuntu 更新后,我收到“未找到 CUDA”错误。啊,我已经使用 .run 文件在这台机器上安装了几次 NVIDA 工具包、驱动程序和 CUDA。再次阅读“NVIDIA CUDA Linux 入门指南”文档后,我决定尝试安装包管理器,因此按照文档中的指示卸载了以前的 .run 安装文件。手册说我应该先给出这个命令。

sudo dpkg -i cuda-repo-<distro>_<version>_<architecture>.deb

但我不知道如何替换distro versionarchitecture
查看 uname 和 lsb_release 结果。

ckim@abnc:~$ uname -a
Linux abnc 4.4.0-34-generic #53~14.04.1-Ubuntu SMP Wed Jul 27 16:56:40 UTC 2016 x86_64 x86_64 x86_64 GNU/Linux

ckim@abnc:~$ lsb_release -a
No LSB modules are available.
Distributor ID: Ubuntu
Description:    Ubuntu 14.04.5 LTS
Release:    14.04
Codename:   trusty

我试过了sudo dpkg -i cuda-repo-14.04_7.5_x86_64.deb,但没用。命令应该是什么?(我试过 amd64 而不是 x86_64,但徒劳无功)。来自http://www.r-tutor.com/gpu-computing/cuda-installation/cuda7.5-ubuntu,我猜是的,sudo dpkg -i cuda-repo-ubuntu1404_7.5-18_x86_64.deb但它也失败了。(我之前使用.run文件安装了cuda7.5-18)

编辑:问题是我没有按照文档中预安装步骤的指示下载实际的 .deb 文件。请参阅下面的评论。有关 .run 文件安装,请参阅 @Terrance 的回答。

答案1

为了安装 DEB 文件,您需要实际下载它。该指南有一个 CUDA 下载站点的链接:http://developer.nvidia.com/cuda-downloads

答案2

以下是我最近做的一件事情,希望对你有帮助。


NVIDIA-370ppa中的驱动程序实际上graphics-drivers带有 CUDA 库。

首先,设置graphics-driversppa:

sudo add-apt-repository ppa:graphics-drivers/ppa

然后更新并安装驱动程序:

sudo apt update
sudo apt install nvidia-370

转到你的~/Downloads/文件夹,然后下载 cuda 运行包:

cd ~/Downloads
wget https://developer.nvidia.com/compute/cuda/8.0/prod/local_installers/cuda_8.0.44_linux-run

重命名新下载的文件:

mv cuda_8.0.44_linux-run cuda_8.0.44_linux.run

然后创建一个用于 cuda 工具箱的目录:

mkdir ~/Downloads/nvidia_installers

然后将安装程序的不同部分提取到文件夹中(必须是完整的目录名):

sh cuda_8.0.44_linux.run -extract=/home/<username>/Downloads/nvidia_installers/

转到 nvidia 文件夹:

cd nvidia_installers/

安装示例和运行时:

sudo sh cuda-linux64-rel-8.0.44-21122537.run
sudo sh cuda-samples-linux-8.0.44-21122537.run

您不需要驱动程序,因为它们已经安装好了。

然后测试您的安装,请访问:

cd /usr/local/cuda-8.0/samples/1_Utilities/deviceQuery

将所有文件更改为您拥有:

sudo chown $USER:$USER *

然后运行 ​​make 来编译 deviceQuery:

sudo make

然后您应该能够运行来deviceQuery显示以下信息:

terrance@terrance-ubuntu:/usr/local/cuda-8.0/samples/1_Utilities/deviceQuery$ ./deviceQuery 
./deviceQuery Starting...

 CUDA Device Query (Runtime API) version (CUDART static linking)

Detected 1 CUDA Capable device(s)

Device 0: "GeForce GTX 560 Ti"
  CUDA Driver Version / Runtime Version          8.0 / 8.0
  CUDA Capability Major/Minor version number:    2.1
  Total amount of global memory:                 959 MBytes (1005387776 bytes)
  ( 8) Multiprocessors, ( 48) CUDA Cores/MP:     384 CUDA Cores
  GPU Max Clock rate:                            1700 MHz (1.70 GHz)
  Memory Clock rate:                             2100 Mhz
  Memory Bus Width:                              256-bit
  L2 Cache Size:                                 524288 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:                     Yes
  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 / 2 / 0
  Compute Mode:
     < Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >

deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 8.0, CUDA Runtime Version = 8.0, NumDevs = 1, Device0 = GeForce GTX 560 Ti
Result = PASS

希望这可以帮助!

相关内容