Ubuntu18 查看CUDA的CUDA_ARCH_BIN

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VS2019 OpenCV 4.4 CUDA10.0 编译中的坑 WIN10 VS2019编译OpenCV 4.4 + CUDA10.0 遇到的坑。大体步骤网上很多细节不写了，主要写下其中遇到的几个坑。一.CUDA_ARCH_BIN 一定填写修改 CUDA_ARCH_BIN 的值（显卡算力值*10），否则编译成功后运行也会出错。下面是官网提供算力表，截了一部分，没有合适自己的显卡可以官网查。 https://developer.nvidia.com/zh-cn/cuda-gpus 二. VS与CUDA的对应关系 CUDA源码中会对VS版本做一些限制，就像本阅读详情

AI摘要

本文介绍了如何通过cuda设备查询工具、cuda samples、官网查询及jetson平台工具获取CUDA_ARCH_BIN值，以确保在编译OpenCV时针对特定显卡优化。步骤包括运行deviceQuery，查看CUDA能力和核心数等关键信息。

我们在使用源码编译带cuda的opencv时，需要设置显卡的CUDA_ARCH_BIN，本文介绍一下获得该值的方法

方法一

安装好cuda之后，可以从cuda sample中获得

cd /usr/local/cuda/samples/1_Utilities/deviceQuery
sudo make
./deviceQuery

如上，运行后输出信息如下

nvidia@nvidia-X10SRA:/usr/local/cuda/samples/1_Utilities/deviceQuery$ ./deviceQuery
./deviceQuery Starting...
CUDA Device Query (Runtime API) version (CUDART static linking)
Detected 3 CUDA Capable device(s)
Device 0: "Tesla T4"
CUDA Driver Version / Runtime Version 10.2 / 10.2
CUDA Capability Major/Minor version number: 7.5
Total amount of global memory: 15110 MBytes (15843721216 bytes)
(40) Multiprocessors, ( 64) CUDA Cores/MP: 2560 CUDA Cores
GPU Max Clock rate: 1590 MHz (1.59 GHz)
Memory Clock rate: 5001 Mhz
Memory Bus Width: 256-bit
L2 Cache Size: 4194304 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: 1024
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 3 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: Enabled
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 / 2 / 0
Compute Mode:
< Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
……