根据blog装好mx250的显卡之后,开始安装cuda
安装教程参考https://blog.csdn.net/weixin_41851439/article/details/88712465
0 确定自己已经装好显卡了 nvidia-smi会显示出来
1 下载cuda和cudnn
上面是9.0的链接
下面是cudnn的链接 需要注册之后才能下载 下载9.0对应版本
https://developer.nvidia.com/rdp/cudnn-archive
把安装包和四个补丁全下载了
2 下载的过程中可以把gcc 和 g++降级 因为cuda需要低版本的
sudo apt-get install gcc-4.8
sudo apt-get install g++-4.8
然后进入到/usr/bin目录下输入:ls -l gcc*
cd /usr/bin
ls -l gcc*
显示结果如下:
lrwxrwxrwx 1 root root 7th 3月 20 11:38 /usr/bin/gcc -> gcc-7
表示gcc链接到gcc-7, 需要将它改为链接到gcc-4.8,方法如下:
sudo mv gcc gcc.bak #备份
sudo ln -s gcc-4.8 gcc #重新链接
同理, 将g++链接到g++4.8:
sudo mv g++ g++.bak
sudo ln -s g++-4.8 g++
在/usr/bin目录下查看gcc和g++版本
ls -l gcc*
ls -l g++*
显示gcc和g++均链接到4.8版本,则说明安装成功
3 安装cuda
下载好了之后 cd到downloads目录 运行.run文件
sudo sh cuda_9.0.176_384.81_linux.run
然后一路accept或者yes,在提示是否安装显卡驱动时选择no(因为已经安装过了,否则可能会出现bug)
会提示驱动问题 不管他 继续
接下来安装补丁文件,方法和安装cuda9.0一样:
sudo sh cuda_9.0.176.1_linux.run
sudo sh cuda_9.0.176.2_linux.run
sudo sh cuda_9.0.176.3_linux.run
sudo sh cuda_9.0.176.4_linux.run
4 配置环境
打开.barshrc
sudo vim ~/.barshrc
在最后面加入下面两条语句
export PATH=/usr/local/cuda-9.0/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda-9.0/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
5 安装cudnn
cd到自己的downloads目录 里面解压:
tar zxvf cudnn-9.0-linux-x64-v7.1.tgz
文件copy到cuda里面
sudo cp /home/**/Downloads/cuda/include/cudnn.h /usr/local/cuda-9.0/include
sudo cp /home/***/Downloads/cuda/lib64/libcudnn* /usr/local/cuda-9.0/lib64
sudo chmod a+r /home/***/Downloads/cuda/include/cudnn.h /usr/local/cuda-9.0/lib64/libcudnn*
OK了
测试cuda是否安装好
cd /usr/local/cuda/samples/1_Utilities/deviceQuery #由自己电脑目录决定
sudo make
sudo ./deviceQuery
出现一长串说明OK
我的是这样
sudo ./deviceQuery
./deviceQuery Starting...
CUDA Device Query (Runtime API) version (CUDART static linking)
Detected 1 CUDA Capable device(s)
Device 0: "GeForce MX250"
CUDA Driver Version / Runtime Version 10.2 / 9.0
CUDA Capability Major/Minor version number: 6.1
Total amount of global memory: 2003 MBytes (2099904512 bytes)
( 3) Multiprocessors, (128) CUDA Cores/MP: 384 CUDA Cores
GPU Max Clock rate: 1582 MHz (1.58 GHz)
Memory Clock rate: 3004 Mhz
Memory Bus Width: 64-bit
L2 Cache Size: 524288 bytes
Maximum Texture Dimension Size (x,y,z) 1D=(131072), 2D=(131072, 65536), 3D=(16384, 16384, 16384)
Maximum Layered 1D Texture Size, (num) layers 1D=(32768), 2048 layers
Maximum Layered 2D Texture Size, (num) layers 2D=(32768, 32768), 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: 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
Supports Cooperative Kernel Launch: Yes
Supports MultiDevice Co-op Kernel Launch: 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 = 10.2, CUDA Runtime Version = 9.0, NumDevs = 1
Result = PASS