Install CUDA 8.02018/01/27 |
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Install GPU Computing Platform (GPGPU (General-Purpose computing on Graphics Processing Units)),
CUDA (Compute Unified Device Architecture) provided by NVIDIA.
To use CUDA, it needs your computer has NVIDIA Graphic cards and also they are the CUDA-Enabled products.
Make sure the details on the site below. (most products are ready in the past few years) ⇒ https://developer.nvidia.com/cuda-gpus |
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Download CUDA Repository RPM package from the site below and Install it.
⇒ https://developer.nvidia.com/cuda-downloads?target_os=Linux&target_arch=x86_64&target_distro=CentOS&target_version=7&target_type=rpmnetwork |
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[root@dlp ~]# rpm -Uvh cuda-repo-rhel7-8.0.61-1.x86_64.rpm Preparing... ################################# [100%] Updating / installing... 1:cuda-repo-rhel7-8.0.61-1 ################################# [100%] # disable usually [root@dlp ~]# sed -i -e "s/enabled=1/enabled=0/g" /etc/yum.repos.d/cuda.repo
# install from CUDA, EPEL
[root@dlp ~]#
yum --enablerepo=cuda,epel install cuda-8-0 xorg-x11-drv-nvidia dkms gcc make
[root@dlp ~]#
vi /etc/profile.d/cuda80.sh # create new 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}} # restart once [root@dlp ~]# reboot
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| [3] | Verify installation with a common user to run sample program. |
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# copy samples [cent@dlp ~]$ cuda-install-samples-8.0.sh ./ Copying samples to ./NVIDIA_CUDA-8.0_Samples now... Finished copying samples.
[cent@dlp ~]$
cd ./NVIDIA_CUDA-8.0_Samples/1_Utilities/deviceQuery
# compile deviceQuery sample [cent@dlp deviceQuery]$ make
# run deviceQuery sample [cent@dlp deviceQuery]$ ./deviceQuery
./deviceQuery Starting...
CUDA Device Query (Runtime API) version (CUDART static linking)
Detected 1 CUDA Capable device(s)
Device 0: "GeForce GTX 1060 6GB"
CUDA Driver Version / Runtime Version 9.1 / 8.0
CUDA Capability Major/Minor version number: 6.1
Total amount of global memory: 6078 MBytes (6373179392 bytes)
(10) Multiprocessors, (128) CUDA Cores/MP: 1280 CUDA Cores
GPU Max Clock rate: 1848 MHz (1.85 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: No
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 / 3 / 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 = 8.0,
NumDevs = 1, Device0 = GeForce GTX 1060 6GB
Result = PASS
# try to run bandwidthTest sample [cent@dlp deviceQuery]$ cd ~/NVIDIA_CUDA-8.0_Samples/1_Utilities/bandwidthTest [cent@dlp bandwidthTest]$ make [cent@dlp bandwidthTest]$ ./bandwidthTest [CUDA Bandwidth Test] - Starting... Running on... Device 0: GeForce GTX 1060 6GB Quick Mode Host to Device Bandwidth, 1 Device(s) PINNED Memory Transfers Transfer Size (Bytes) Bandwidth(MB/s) 33554432 6108.4 Device to Host Bandwidth, 1 Device(s) PINNED Memory Transfers Transfer Size (Bytes) Bandwidth(MB/s) 33554432 6531.4 Device to Device Bandwidth, 1 Device(s) PINNED Memory Transfers Transfer Size (Bytes) Bandwidth(MB/s) 33554432 154639.7 Result = PASS NOTE: The CUDA Samples are not meant for performance measurements. Results may vary when GPU Boost is enabled. |
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