Ubuntu 22.04
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NVIDIA : CUDA 11.5 インストール2022/08/29

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
[2] Ubuntu 22.04 公式リポジトリで提供されている CUDA 11.5 をインストールします。
apt -y install nvidia-cuda-toolkit
nvcc --version

nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2021 NVIDIA Corporation
Built on Thu_Nov_18_09:45:30_PST_2021
Cuda compilation tools, release 11.5, V11.5.119
Build cuda_11.5.r11.5/compiler.30672275_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。
# サンプルプログラムをコピー

git clone https://github.com/NVIDIA/cuda-samples.git

cd ./cuda-samples/Samples/1_Utilities/deviceQuery
vi Makefile
# 35行目:変更

# deviceQuery サンプル コンパイル

# deviceQuery サンプル 実行


./deviceQuery Starting...

 CUDA Device Query (Runtime API) version (CUDART static linking)

Detected 1 CUDA Capable device(s)

Device 0: "NVIDIA GeForce GTX 1060 6GB"
  CUDA Driver Version / Runtime Version          11.6 / 11.5
  CUDA Capability Major/Minor version number:    6.1
  Total amount of global memory:                 6078 MBytes (6373376000 bytes)
  (010) 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 shared memory per multiprocessor:        98304 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 = 11.6, CUDA Runtime Version = 11.5, NumDevs = 1
Result = PASS

# bandwidthTest サンプル テスト

cd ~/cuda-samples/Samples/1_Utilities/bandwidthTest
vi Makefile
# 35行目:変更



[CUDA Bandwidth Test] - Starting...
Running on...

 Device 0: NVIDIA GeForce GTX 1060 6GB
 Quick Mode

 Host to Device Bandwidth, 1 Device(s)
 PINNED Memory Transfers
   Transfer Size (Bytes)        Bandwidth(GB/s)
   32000000                     6.3

 Device to Host Bandwidth, 1 Device(s)
 PINNED Memory Transfers
   Transfer Size (Bytes)        Bandwidth(GB/s)
   32000000                     6.7

 Device to Device Bandwidth, 1 Device(s)
 PINNED Memory Transfers
   Transfer Size (Bytes)        Bandwidth(GB/s)
   32000000                     30.7

Result = PASS

NOTE: The CUDA Samples are not meant for performance measurements. Results may vary when GPU Boost is enabled.