『heqingchun-ubuntu系统下安装cuda与cudnn』
ubuntu系统下安装cuda与cudnn
一、安装依赖
1.更新
sudo apt update
sudo apt upgrade -y
2.基础工具
sudo apt install -y build-essential python
二、安装CUDA
1.文件下载
网址
https://developer.nvidia.com/cuda-toolkit-archive
依次点击
(1)“CUDA Toolkit 11.6.2”
(2)“Linux”
(3)“x86_64”
(4)“Ubuntu”
(5)“20.04”
(6)“runfile(local)”
在"Installation Instructions:"下方为下载安装指令
下载指令(文件需下载到英文路径)，如：
cd /home/heqingchun/soft/nvidia
wget https://developer.download.nvidia.com/compute/cuda/11.6.2/local_installers/cuda_11.6.2_510.47.03_linux.run
在“/home/heqingchun/soft/nvidia”路径中下载得到“cuda_11.6.2_510.47.03_linux.run”文件
以下是安装时使用的指令
sudo sh cuda_11.6.2_510.47.03_linux.run
2.cuda安装
(1)赋予可执行权限
chmod 755 cuda_11.6.2_510.47.03_linux.run
(2)运行安装
sudo sh cuda_11.6.2_510.47.03_linux.run
期间会弹出对话框，需手动输入"accept"回车，在之后再弹出对话框中取消勾选“Driver”
CUDA Installer │
│ - [ ] Driver │
│ [ ] 510.47.03 │
│ + [X] CUDA Toolkit 11.6 │
│ [X] CUDA Samples 11.6 │
│ [X] CUDA Demo Suite 11.6 │
│ [X] CUDA Documentation 11.6 │
│ Options │
│ Install
向下选择"install"后等待安装完毕即可。
安装完毕信息：
===========
= Summary =
===========
Driver: Not Selected
Toolkit: Installed in /usr/local/cuda-11.6/
Please make sure that
- PATH includes /usr/local/cuda-11.6/bin
- LD_LIBRARY_PATH includes /usr/local/cuda-11.6/lib64, or, add /usr/local/cuda-11.6/lib64 to /etc/ld.so.conf and run ldconfig as root
To uninstall the CUDA Toolkit, run cuda-uninstaller in /usr/local/cuda-11.6/bin
***WARNING: Incomplete installation! This installation did not install the CUDA Driver. A driver of version at least 510.00 is required for CUDA 11.6 functionality to work.
To install the driver using this installer, run the following command, replacing with the name of this run file:
sudo .run --silent --driver
Logfile is /var/log/cuda-installer.log
(3)配置环境变量
str='export PATH=/usr/local/cuda-11.6/bin:"$"PATH' && \
sudo sh -c "echo $str >> /etc/profile" && \
source /etc/profile && \
str='export LD_LIBRARY_PATH=/usr/local/cuda-11.6/lib64:"$"LD_LIBRARY_PATH' && \
sudo sh -c "echo $str >> /etc/profile" && \
source /etc/profile
(4)重启电脑
3.验证安装
(1)版本信息
nvcc -V
显示如下:
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2022 NVIDIA Corporation
Built on Tue_Mar__8_18:18:20_PST_2022
Cuda compilation tools, release 11.6, V11.6.124
Build cuda_11.6.r11.6/compiler.31057947_0
(2)库信息
cat /usr/local/cuda/version.json
显示如下:
{
"cuda" : {
"name" : "CUDA SDK",
"version" : "11.6.20220318"
},
"cuda_cccl" : {
"name" : "CUDA C++ Core Compute Libraries",
"version" : "11.6.55"
},
"cuda_cudart" : {
"name" : "CUDA Runtime (cudart)",
"version" : "11.6.55"
},
"cuda_cuobjdump" : {
"name" : "cuobjdump",
"version" : "11.6.124"
},
"cuda_cupti" : {
"name" : "CUPTI",
"version" : "11.6.124"
},
"cuda_cuxxfilt" : {
"name" : "CUDA cu++ filt",
"version" : "11.6.124"
},
"cuda_demo_suite" : {
"name" : "CUDA Demo Suite",
"version" : "11.6.55"
},
"cuda_gdb" : {
"name" : "CUDA GDB",
"version" : "11.6.124"
},
"cuda_memcheck" : {
"name" : "CUDA Memcheck",
"version" : "11.6.124"
},
"cuda_nsight" : {
"name" : "Nsight Eclipse Plugins",
"version" : "11.6.124"
},
"cuda_nvcc" : {
"name" : "CUDA NVCC",
"version" : "11.6.124"
},
"cuda_nvdisasm" : {
"name" : "CUDA nvdisasm",
"version" : "11.6.124"
},
"cuda_nvml_dev" : {
"name" : "CUDA NVML Headers",
"version" : "11.6.55"
},
"cuda_nvprof" : {
"name" : "CUDA nvprof",
"version" : "11.6.124"
},
"cuda_nvprune" : {
"name" : "CUDA nvprune",
"version" : "11.6.124"
},
"cuda_nvrtc" : {
"name" : "CUDA NVRTC",
"version" : "11.6.124"
},
"cuda_nvtx" : {
"name" : "CUDA NVTX",
"version" : "11.6.124"
},
"cuda_nvvp" : {
"name" : "CUDA NVVP",
"version" : "11.6.124"
},
"cuda_samples" : {
"name" : "CUDA Samples",
"version" : "11.6.101"
},
"cuda_sanitizer_api" : {
"name" : "CUDA Compute Sanitizer API",
"version" : "11.6.124"
},
"libcublas" : {
"name" : "CUDA cuBLAS",
"version" : "11.9.2.110"
},
"libcufft" : {
"name" : "CUDA cuFFT",
"version" : "10.7.2.124"
},
"libcurand" : {
"name" : "CUDA cuRAND",
"version" : "10.2.9.124"
},
"libcusolver" : {
"name" : "CUDA cuSOLVER",
"version" : "11.3.4.124"
},
"libcusparse" : {
"name" : "CUDA cuSPARSE",
"version" : "11.7.2.124"
},
"libnpp" : {
"name" : "CUDA NPP",
"version" : "11.6.3.124"
},
"libnvjpeg" : {
"name" : "CUDA nvJPEG",
"version" : "11.6.2.124"
},
"nsight_compute" : {
"name" : "Nsight Compute",
"version" : "2022.1.1.2"
},
"nsight_systems" : {
"name" : "Nsight Systems",
"version" : "2021.5.2.53"
},
"nvidia_driver" : {
"name" : "NVIDIA Linux Driver",
"version" : "510.47.03"
}
}
(3)计算能力
cd /usr/local/cuda/extras/demo_suite
./deviceQuery
显示:
deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 11.6, CUDA Runtime Version = 11.6, NumDevs = 1, Device0 = NVIDIA GeForce RTX 3050 Laptop GPU
Result = PASS
CUDA安装完毕
三、安装cuDNN
1.文件下载
网址
https://developer.nvidia.com/rdp/cudnn-archive
依次点击
(1)“Download cuDNN v8.4.0 (April 1st, 2022), for CUDA 11.x”
(2)“Local Installer for Linux x86_64 (Tar)”
注:需要登陆，登陆成功后即可下载
下载得到“cudnn-linux-x86_64-8.4.0.27_cuda11.6-archive.tar.xz”文件放入“/home/heqingchun/soft/nvidia”目录
2.cuDNN安装
进入文件所在目录、解压文件、解压后进入文件夹、拷贝文件
cd /home/heqingchun/soft/nvidia
tar -xvf cudnn-linux-x86_64-8.4.0.27_cuda11.6-archive.tar.xz && \
cd cudnn-linux-x86_64-8.4.0.27_cuda11.6-archive && \
sudo cp include/* /usr/local/cuda-11.6/include && \
sudo cp -P lib/* /usr/local/cuda-11.6/lib64 && \
sudo chmod a+r /usr/local/cuda-11.6/include/cudnn*.h /usr/local/cuda-11.6/lib64/libcudnn*
重启电脑
3.验证安装
cat /usr/local/cuda/include/cudnn_version.h
显示如下:
/**
* \file: The master cuDNN version file.
*/
#ifndef CUDNN_VERSION_H_
#define CUDNN_VERSION_H_
#define CUDNN_MAJOR 8
#define CUDNN_MINOR 4
#define CUDNN_PATCHLEVEL 0
#define CUDNN_VERSION (CUDNN_MAJOR * 1000 + CUDNN_MINOR * 100 + CUDNN_PATCHLEVEL)
#endif /* CUDNN_VERSION_H */
cuDNN安装完毕
ubuntu系统下安装cuda与cudnn-完毕