通过ppa源安装
添加源
sudo add-apt-repository ppa:graphics-drivers/ppa
sudo apt update
检测显卡版本及推荐的驱动
$ ubuntu-drivers devices
== /sys/devices/pci0000:00/0000:00:01.0/0000:01:00.0 ==
modalias : pci:v000010DEd00001C20sv000017AAsd000039F5bc03sc00i00
vendor : NVIDIA Corporation
model : GP106M [GeForce GTX 1060 Mobile]
driver : nvidia-driver-390 - third-party free
driver : nvidia-driver-415 - third-party free recommended
driver : nvidia-driver-396 - third-party free
driver : nvidia-driver-410 - third-party free
driver : xserver-xorg-video-nouveau - distro free builtin
安装
可以直接安装推荐的驱动或者别的版本，这里用410是因为cuda10.0 需要。
sudo apt install nvidia-410
重启
检测
nvidia-smi
Fri Jan 18 19:19:58 2019
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 410.78 Driver Version: 410.78 CUDA Version: 10.0 |
|-------------------------------+----------------------+----------------------+
| 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 1060 Off | 00000000:01:00.0 Off | N/A |
| N/A 54C P3 17W / N/A | 366MiB / 6078MiB | 2% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| 0 3109 G /usr/lib/xorg/Xorg 165MiB |
| 0 3510 G /usr/bin/gnome-shell 105MiB |
| 0 3972 G ...uest-channel-token=11444502369567668681 93MiB |
+-----------------------------------------------------------------------------+
cuda
CUDA（Compute Unified Device Architecture，统一计算架构[1]）是由NVIDIA所推出的一种集成技术，是该公司对于GPGPU的正式名称。透过这个技术，用户可利用NVIDIA的GeForce 8以后的GPU和较新的Quadro GPU进行计算。亦是首次可以利用GPU作为C-编译器的开发环境。NVIDIA营销的时候，往往将编译器与架构混合推广，造成混乱。实际上，CUDA可以兼容OpenCL或者自家的C-编译器。无论是CUDA C-语言或是OpenCL，指令最终都会被驱动程序转换成PTX代码，交由显示核心计算。
cuda官网。
选择最新的10.0版本，按照如下，选择runfile，下载安装。
1
安装依赖
sudo apt-get install linux-headers-$(uname -r) build-essential
sudo dpkg -i cuda-repo-ubuntu1804-10-0-local-10.0.130-410.48_1.0-1_amd64.deb
# 根据提示添加GPG key
sudo apt-key add /var/cuda-repo-<version>/7fa2af80.pub
sudo apt update
sudo apt install cuda
设置环境变量
在~/.bashrc 最后添加：
export PATH=/usr/local/cuda-10.0/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda-10.0/lib64\
${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
source ~/.bashrc
测试
cat /proc/driver/nvidia/version
NVRM version: NVIDIA UNIX x86_64 Kernel Module 410.78 Sat Nov 10 22:09:04 CST 2018
GCC version: gcc version 7.3.0 (Ubuntu 7.3.0-27ubuntu1~18.04)
编译样例
cp -r /usr/local/cuda-10.0/samples/ ~
cd ~/samples
make
# 编译完成后
cd bin/x86_64/linux/release/
./deviceQuery
# 输出如下：
./deviceQuery Starting...
CUDA Device Query (Runtime API) version (CUDART static linking)
Detected 1 CUDA Capable device(s)
Device 0: "GeForce GTX 1060"
CUDA Driver Version / Runtime Version 10.0 / 10.0
CUDA Capability Major/Minor version number: 6.1
Total amount of global memory: 6078 MBytes (6373572608 bytes)
(10) Multiprocessors, (128) CUDA Cores/MP: 1280 CUDA Cores
GPU Max Clock rate: 1671 MHz (1.67 GHz)
Memory Clock rate: 4004 Mhz
Memory Bus Width: 192-bit
L2 Cache Size: 1572864 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
Device supports Compute Preemption: Yes
Supports Cooperative Kernel Launch: Yes
Supports MultiDevice Co-op Kernel Launch: Yes
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 = 10.0, CUDA Runtime Version = 10.0, NumDevs = 1
Result = PASS
编译完成没有错误，测试也通过的话，基本就没有问题了。
