Ubuntu 18.04 安装 CUDA 9.1
安装GCC/G++ - 5
Ubuntu18.04默认GCC-7.3.0，由于CUDA 9.1未支持GCC-7，所以需要安装低版本的5或者<= 6.3.0，并设置为默认版本
sudo apt install gcc-5 g++-5
# 设置默认版本
sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-5 50 --slave /usr/bin/g++ g++ /usr/bin/g++-5
sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-7 70 --slave /usr/bin/g++ g++ /usr/bin/g++-7
sudo update-alternatives --config gcc
此时选择gcc-5为默认版本，输入2：
There are 2 choices for the alternative gcc (providing /usr/bin/gcc).
Selection Path Priority Status
------------------------------------------------------------
* 0 /usr/bin/gcc-7 70 auto mode
1 /usr/bin/gcc-5 50 manual mode
2 /usr/bin/gcc-7 70 manual mode
Press to keep the current choice[*], or type selection number:
检查默认GCC版本
gcc --version
安装NVIDIA驱动
单独安装成功率较高且可以安装最新的驱动
sudo add-apt-repository ppa:graphics-drivers/ppa
sudo apt update
sudo apt install nvidia-390
安装完成后重启，可以确认一下版本
$ cat /proc/driver/nvidia/version
NVRM version: NVIDIA UNIX x86_64 Kernel Module 390.48 Thu Mar 22 00:42:57 PDT 2018
GCC version: gcc version 6.4.0 20180424 (Ubuntu 6.4.0-17ubuntu1)
安装CUDA
下载Ubuntu 17.04版本的cuda_9.1.85_387.26_linux.run，安装时，跳过安装驱动部分。
设置环境变量(用bush则是.bushrc， zsh则是.zshrc)
echo 'export PATH=/usr/local/cuda-9.1/bin:$PATH' >> ~/.zshrc
echo 'export LD_LIBRARY_PATH=/usr/local/cuda-9.1/lib64:$LD_LIBRARY_PATH' >> ~/.zshrc
检查
$ nvidia-smi
Sun Apr 29 18:01:43 2018
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 390.48 Driver Version: 390.48 |
|-------------------------------+----------------------+----------------------+
| 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 GTX 960M Off | 00000000:01:00.0 Off | N/A |
| N/A 63C P8 N/A / N/A | 474MiB / 2004MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| 0 1019 G /usr/lib/xorg/Xorg 24MiB |
| 0 1119 G /usr/bin/gnome-shell 48MiB |
| 0 1380 G /usr/lib/xorg/Xorg 155MiB |
| 0 1606 G /usr/bin/gnome-shell 162MiB |
| 0 2661 G ...-token=1EB02DD7413DCE134FBD8EDB1260A396 72MiB |
| 0 10203 G ...are/jetbrains-toolbox/jetbrains-toolbox 5MiB |
+-----------------------------------------------------------------------------+
$ nvcc -V
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2017 NVIDIA Corporation
Built on Fri_Nov__3_21:07:56_CDT_2017
Cuda compilation tools, release 9.1, V9.1.85
确认CUDA工作
找到samples，一般在home目录下
cd ~/NVIDIA_CUDA-9.1_Samples/
make
等待编译完成，
cd ./bin/x86_64/linux/release
使用deviceQuery 或 bandwidthTest测试
$ ./deviceQuery
./deviceQuery Starting...
CUDA Device Query (Runtime API) version (CUDART static linking)
Detected 1 CUDA Capable device(s)
Device 0: "GeForce GTX 960M"
CUDA Driver Version / Runtime Version 9.1 / 9.1
CUDA Capability Major/Minor version number: 5.0
Total amount of global memory: 2004 MBytes (2101870592 bytes)
( 5) Multiprocessors, (128) CUDA Cores/MP: 640 CUDA Cores
GPU Max Clock rate: 1176 MHz (1.18 GHz)
Memory Clock rate: 2505 Mhz
Memory Bus Width: 128-bit
L2 Cache Size: 2097152 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
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 = 9.1, CUDA Runtime Version = 9.1, NumDevs = 1
Result = PASS
或
$ ./bandwidthTest
[CUDA Bandwidth Test] - Starting...
Running on...
Device 0: GeForce GTX 960M
Quick Mode
Host to Device Bandwidth, 1 Device(s)
PINNED Memory Transfers
Transfer Size (Bytes) Bandwidth(MB/s)
33554432 12339.9
Device to Host Bandwidth, 1 Device(s)
PINNED Memory Transfers
Transfer Size (Bytes) Bandwidth(MB/s)
33554432 11720.0
Device to Device Bandwidth, 1 Device(s)
PINNED Memory Transfers
Transfer Size (Bytes) Bandwidth(MB/s)
33554432 65699.6
Result = PASS
NOTE: The CUDA Samples are not meant for performance measurements. Results may vary when GPU Boost is enabled.
CuDNN
在官网下载.deb安装包直接安装即可。