CUDA 11.0 インストール2020/07/21 |
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NVIDIA 社製グラフィックカードによる GPU コンピューティング GPGPU（General-Purpose computing on Graphics Processing Units) プラットフォーム CUDA (Compute Unified Device Architecture)
をインストールします。
CUDA を利用するにあたっては、グラフィックカードが対応製品である必要があります。詳細は NVIDIA 社のサイトで確認ください。(ここ数年のものであればほぼ対応) ⇒ https://developer.nvidia.com/cuda-gpus |
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| [2] | NVIDIA のダウンロードサイトからリポジトリをダウンロードして CUDA をインストールします。 |
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[root@dlp ~]# dnf config-manager --add-repo http://developer.download.nvidia.com/compute/cuda/repos/rhel8/x86_64/cuda-rhel8.repo Adding repo from: http://developer.download.nvidia.com/compute/cuda/repos/rhel8/x86_64/cuda-rhel8.repo
[root@dlp ~]#
vi /etc/profile.d/cuda110.sh # 新規作成 export PATH=/usr/local/cuda-11.0/bin${PATH:+:${PATH}} export LD_LIBRARY_PATH=/usr/local/cuda-11.0/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}} source /etc/profile.d/cuda110.sh [root@dlp ~]# nvcc --version nvcc: NVIDIA (R) Cuda compiler driver Copyright (c) 2005-2020 NVIDIA Corporation Built on Thu_Jun_11_22:26:38_PDT_2020 Cuda compilation tools, release 11.0, V11.0.194 Build cuda_11.0_bu.TC445_37.28540450_0 |
| [3] | 任意の一般ユーザーでサンプルプログラムを実行して動作確認します。 |
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# サンプルプログラムをコピー [cent@dlp ~]$ cuda-install-samples-11.0.sh ./ Copying samples to ./NVIDIA_CUDA-11.0_Samples now... Finished copying samples.
[cent@dlp ~]$
cd ./NVIDIA_CUDA-11.0_Samples/1_Utilities/deviceQuery
# deviceQuery サンプル コンパイル [cent@dlp deviceQuery]$ make
# deviceQuery サンプル 実行 [cent@dlp deviceQuery]$ ./deviceQuery
./deviceQuery Starting...
CUDA Device Query (Runtime API) version (CUDART static linking)
[ 9264.210981] nvidia-uvm: Loaded the UVM driver, major device number 239.
Detected 1 CUDA Capable device(s)
Device 0: "GeForce GTX 1070"
CUDA Driver Version / Runtime Version 11.0 / 11.0
CUDA Capability Major/Minor version number: 6.1
Total amount of global memory: 8120 MBytes (8513978368 bytes)
(15) Multiprocessors, (128) CUDA Cores/MP: 1920 CUDA Cores
GPU Max Clock rate: 1785 MHz (1.78 GHz)
Memory Clock rate: 4004 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: 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 supports Managed Memory: 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 / 5 / 0
Compute Mode:
< Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 11.0, CUDA Runtime Version = 11.0, NumDevs = 1
Result = PASS
# bandwidthTest サンプル テスト [cent@dlp deviceQuery]$ cd ~/NVIDIA_CUDA-11.0_Samples/1_Utilities/bandwidthTest [cent@dlp bandwidthTest]$ make [cent@dlp bandwidthTest]$ ./bandwidthTest [CUDA Bandwidth Test] - Starting... Running on... Device 0: GeForce GTX 1070 Quick Mode Host to Device Bandwidth, 1 Device(s) PINNED Memory Transfers Transfer Size (Bytes) Bandwidth(GB/s) 32000000 6.2 Device to Host Bandwidth, 1 Device(s) PINNED Memory Transfers Transfer Size (Bytes) Bandwidth(GB/s) 32000000 13.1 Device to Device Bandwidth, 1 Device(s) PINNED Memory Transfers Transfer Size (Bytes) Bandwidth(GB/s) 32000000 195.3 Result = PASS NOTE: The CUDA Samples are not meant for performance measurements. Results may vary when GPU Boost is enabled. |
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