ubuntu19.10安装cuda-10.1

ubuntu19.10安装cuda-10.1

1.安装N卡驱动：

打开ubuntu的软件和更新，设置N卡驱动

2.查看ubuntu显卡驱动

nvidia-smi

显示：

Sun Feb 23 06:41:41 2020
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 430.50       Driver Version: 430.50       CUDA Version: 10.1     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  GeForce 940M        Off  | 00000000:01:00.0 Off |                  N/A |
| N/A   44C    P0    N/A /  N/A |    306MiB /  2004MiB |     28%      Default |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                       GPU Memory |
|  GPU       PID   Type   Process name                             Usage      |
|=============================================================================|
|    0       982      G   /usr/lib/xorg/Xorg                            23MiB |
|    0      1390      G   /usr/lib/xorg/Xorg                           102MiB |
|    0      1613      G   /usr/bin/gnome-shell                          95MiB |
|    0      2036      G   ...AAAAAAAAAAAAAAgAAAAAAAAA --shared-files    34MiB |
+-----------------------------------------------------------------------------+

可以看到

CUDA Version: 10.1

3.我们下载CUDA Version: 10.1

ubuntu系统下cuda的下载推荐XDM下载器

下载后，在安装包目录打开终端输入：

sudo dpkg -i cuda-repo-ubuntu1810-10-1-local-10.1.105-418.39_1.0-1_amd64.deb
sudo apt-key add /var/cuda-repo-10-1-local-10.1.105-418.39/7fa2af80.pub
sudo apt-get update
sudo apt-get install cuda

4.至此安装包安装完成，接下来将cuda加入环境变量：

sudo gedit /etc/profile

export PATH=/usr/local/cuda-10.1/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/cuda-10.1/lib64:$LD_LIBRARY_PATH

source /etc/profile

5.打开安装目录/ usr / local / cuda- 10.1

输入nvcc -V,显示cuda版本:

nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2019 NVIDIA Corporation
Built on Fri_Feb__8_19:08:17_PST_2019
Cuda compilation tools, release 10.1, V10.1.105

6.在编译样例目录/usr/local/cuda-10.1/samples输入make发现出错，出错显示：

make[1]: 进入目录“/usr/local/cuda-10.1/samples/0_Simple/simpleSeparateCompilation”
/usr/local/cuda-10.1/bin/nvcc -ccbin g++ -I../../common/inc  -m64    -dc -gencode arch=compute_30,code=sm_30 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_37,code=sm_37 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_75,code=compute_75 -o simpleDeviceLibrary.o -c simpleDeviceLibrary.cu
In file included from /usr/local/cuda-10.1/bin/../targets/x86_64-linux/include/cuda_runtime.h:83,
                 from <command-line>:
/usr/local/cuda-10.1/bin/../targets/x86_64-linux/include/crt/host_config.h:129:2: error: #error -- unsupported GNU version! gcc versions later than 8 are not supported!
  129 | #error -- unsupported GNU version! gcc versions later than 8 are not supported!
      |  ^~~~~
make[1]: *** [Makefile:290：simpleDeviceLibrary.o] 错误 1
make[1]: 离开目录“/usr/local/cuda-10.1/samples/0_Simple/simpleSeparateCompilation”
make: *** [Makefile:51：0_Simple/simpleSeparateCompilation/Makefile.ph_build] 错误 2

重点在：

error -- unsupported GNU version! gcc versions later than 8 are not supported!

7.原因是ubuntu 19.10 gcc版本过高，所以我们需要使用低于8.0的gcc g++

为了解决这个问题，我们可以下载gcc-7 g++-7来结合 update-alternatives 对样例进行编译

首先安装gcc-7 g++-7

sudo apt-get install gcc-7 g++-7

安装完成后我们开始使用update-alternatives进行版本控制，语法如下：

update-alternatives --install  <链接> <名称> <路径> <优先级>

对于gcc有，命令行末尾的数字表优先级，数字越大优先级越高

sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-7 10
sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-9 20

版本设置：

sudo update-alternatives --config gcc

显示：

有 2 个候选项可用于替换 gcc (提供 /usr/bin/gcc)。

  选择       路径          优先级  状态
------------------------------------------------------------
* 0            /usr/bin/gcc-9   20        自动模式
  1            /usr/bin/gcc-7   10        手动模式
  2            /usr/bin/gcc-9   20        手动模式

要维持当前值[*]请按<回车键>，或者键入选择的编号：1（我选的1）
update-alternatives: 使用 /usr/bin/gcc-7 来在手动模式中提供 /usr/bin/gcc (gcc)

对于g++

sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-7 10
sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-9 20

版本设置：

sudo update-alternatives --config g++

显示：

有 2 个候选项可用于替换 g++ (提供 /usr/bin/g++)。

  选择       路径          优先级  状态
------------------------------------------------------------
* 0            /usr/bin/g++-9   20        自动模式
  1            /usr/bin/g++-7   10        手动模式
  2            /usr/bin/g++-9   20        手动模式

要维持当前值[*]请按<回车键>，或者键入选择的编号：1（对的我摁的1,就是我）
update-alternatives: 使用 /usr/bin/g++-7 来在手动模式中提供 /usr/bin/g++ (g++)

8.将gcc与g++都切换成gcc-7 g++-7后就可以在样例目录下输入make编译啦

编译完成后，生成的bin文件夹里找到deviceQuery 那一级目录，输入

./deviceQuery 

看到类似的即为成功安装：

./deviceQuery Starting...

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

Detected 1 CUDA Capable device(s)

Device 0: "GeForce 940M"
  CUDA Driver Version / Runtime Version          10.1 / 10.1
  CUDA Capability Major/Minor version number:    5.0
  Total amount of global memory:                 2004 MBytes (2101870592 bytes)
  ( 3) Multiprocessors, (128) CUDA Cores/MP:     384 CUDA Cores
  GPU Max Clock rate:                            1176 MHz (1.18 GHz)
  Memory Clock rate:                             1001 Mhz
  Memory Bus Width:                              64-bit
  L2 Cache Size:                                 1048576 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 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 supports Compute Preemption:            No
  Supports Cooperative Kernel Launch:            No
  Supports MultiDevice Co-op Kernel Launch:      No
  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 = 10.1, CUDA Runtime Version = 10.1, NumDevs = 1
Result = PASS

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