懶人版方法:
apt-key adv --fetch-keys http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/7fa2af80.pub
echo "deb http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64 /" | sudo tee /etc/apt/sources.list.d/cuda.list
sudo apt-get update
sudo apt-get -y install cuda-drivers cuda
這個方法會安裝穩定版的驅動和CUDA,可能不那麼新。
然後開始安裝 cuDNN, 先下載 cuDNN 6.0,
wget http://developer.download.nvidia.com/compute/redist/cudnn/v6.0/cudnn-8.0-linux-x64-v6.0.tgz
然後解壓到 /usr/local
sudo tar -zxf cudnn-8.0-linux-x64-v6.0.tgz -P /usr/local
至此,驅動, CUDA 和 cuDNN都安裝完了。
如果你想安裝最新版的驅動和最新版的CUDA,那麼接著讀下去吧。
sudo add-apt-repository -qy ppa:graphics-drivers/ppa
sudo apt-get -qy update
sudo apt-get -qy install nvidia-370
sudo apt-get -qy install mesa-common-dev
sudo apt-get -qy install freeglut3-dev
sudo reboot
注意,一般比較新的主板,默認是UEFI BIOS,默認啟用了 Secure Boot,否則開機後登陸不進去。老主板沒有這個問題。
去 CUDA 8.x 下載頁面,一定要下載 runfile 安裝方式的安裝包,參考資料裡的好幾篇都是選擇這種方式,貌似 deb包有坑?
chmod u+x ./cuda_8.0.27_linux.run
sudo ./cuda_8.0.27_linux.run --tmpdir=/tmp
執行後會有一系列提示讓你確認,第一個就是問你是否安裝顯卡驅動,由於前一步已經安裝了顯卡驅動,所以這裡就不需要了,況且 runfile 自帶的驅動版本不是最新的。 因此 Install NVIDIA Accelerated Graphics Driver for Linux-x86_64 361.77? 這裡選擇 no。
Do you accept the previously read EULA?
accept/decline/quit: accept
Install NVIDIA Accelerated Graphics Driver for Linux-x86_64 361.77?
(y)es/(n)o/(q)uit: n
Install the CUDA 8.0 Toolkit?
(y)es/(n)o/(q)uit: y
Enter Toolkit Location
[ default is /usr/local/cuda-8.0 ]:
Do you want to install a symbolic link at /usr/local/cuda?
(y)es/(n)o/(q)uit: y
Install the CUDA 8.0 Samples?
(y)es/(n)o/(q)uit: y
Enter CUDA Samples Location
[ default is /home/programmer ]:
你以為你會成功安裝嗎?並不是,你一定會碰到一個錯誤,Installation Failed. Using unsupported Compiler. ,這是因為 Ubuntu 16.04 默認的 GCC 5.4 對於 CUDA 8.x來說過於新了,CUDA 安裝腳本還不能識別新版本的 GCC。
看了一下安裝日誌,解決方案也很簡單,加一個 --override 選項,
sudo ./cuda_8.0.27_linux.run --tmpdir=/tmp --override
這次可以成功了。
===========
= Summary =
===========
Driver: Not Selected
Toolkit: Installed in /usr/local/cuda-8.0
Samples: Installed in /home/programmer, but missing recommended libraries
Please make sure that
- PATH includes /usr/local/cuda-8.0/bin
- LD_LIBRARY_PATH includes /usr/local/cuda-8.0/lib64, or, add /usr/local/cuda-8.0/lib64 to /etc/ld.so.conf and run ldconfig as root
To uninstall the CUDA Toolkit, run the uninstall script in /usr/local/cuda-8.0/bin
Please see CUDA_Installation_Guide_Linux.pdf in /usr/local/cuda-8.0/doc/pdf for detailed information on setting up CUDA.
***WARNING: Incomplete installation! This installation did not install the CUDA Driver. A driver of version at least 361.00 is required for CUDA 8.0 functionality to work.
To install the driver using this installer, run the following command, replacing <CudaInstaller> with the name of this run file:
sudo <CudaInstaller>.run -silent -driver
Logfile is /tmp/cuda_install_6794.log
Signal caught, cleaning up
把以下兩行加入到 .bashrc
export PATH=/usr/local/cuda-8.0/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda-8.0/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
chmod u+x ./cuda_8.0.27.1_linux.run
sudo ./cuda_8.0.27.1_linux.run
測試是否安裝成功
最後再來測試一下CUDA,運行:
nvidia-smi
Sat Jun 3 13:36:13 2017
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 375.39 Driver Version: 375.39 |
|-------------------------------+----------------------+----------------------+
| 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 660 Off | 0000:01:00.0 N/A | N/A |
| 31% 43C P8 N/A / N/A | 646MiB / 1991MiB | N/A Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| 0 Not Supported |
+-----------------------------------------------------------------------------+
再來試幾個CUDA例子:
cd ~/NVIDIA_CUDA-8.0_Samples/1_Utilities/deviceQuery
make
執行 ./deviceQuery,得到:
CUDA Device Query (Runtime API) version (CUDART static linking)
Detected 1 CUDA Capable device(s)
Device 0: "GeForce GTX 1080"
CUDA Driver Version / Runtime Version 8.0 / 8.0
CUDA Capability Major/Minor version number: 6.1
Total amount of global memory: 8110 MBytes (8504279040 bytes)
(20) Multiprocessors, (128) CUDA Cores/MP: 2560 CUDA Cores
GPU Max Clock rate: 1734 MHz (1.73 GHz)
Memory Clock rate: 5005 Mhz
Memory Bus Width: 256-bit
L2 Cache Size: 2097152 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 PCI Domain ID / Bus ID / location ID: 0 / 5 / 0
Compute Mode:
< Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 8.0, CUDA Runtime Version = 8.0, NumDevs = 1, Device0 = GeForce GTX 1080
Result = PASS
再測試試一下nobody:
cd ~/NVIDIA_CUDA-8.0_Samples/5_Simulations/nbody/
make
執行:
./nbody -benchmark -numbodies=256000 -device=0
得到:
> Windowed mode
> Simulation data stored in video memory
> Single precision floating point simulation
> 1 Devices used for simulation
gpuDeviceInit() CUDA Device [0]: "GeForce GTX 1080
> Compute 6.1 CUDA device: [GeForce GTX 1080]
number of bodies = 256000
256000 bodies, total time for 10 iterations: 2364.286 ms
= 277.192 billion interactions per second
= 5543.830 single-precision GFLOP/s at 20 flops per interaction
至此,說明 CUDA 8.x 安裝成功了。