c – 关于CUDA的架构(SM,SP)

我是一个刚刚开始CUDA编程的人.
似乎有SP SM和CUDA架构的概念.
我试着运行样本源的deviceQuery.cpp我觉得什么有效,SP SM开发他们的环境,
已经不知道哪个项目SP是否是SM中的任何项目.

我认为项目“(14)多处理器,(8)CUDA核心/ MP”并且对SP和SM都是正确的,但我将正确理解以下内容？

SM = Multiprocessors = 14
SP = CUDA Cores/MP = 8
CUDA Cores = 14 * 8 = 112

顺便说一下,deviceQuery.cpp的结果如下.

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

Detected 1 CUDA Capable device(s)

Device 0: “GeForce GTS 240
CUDA Driver Version / Runtime Version 5.5 / 5.5
CUDA Capability Major/Minor version number: 1.1
Total amount of global memory: 1024 MBytes (1073741824 bytes)
(14) Multiprocessors, ( 8) CUDA Cores/MP: 112 CUDA Cores
GPU Clock rate: 1620 MHz (1.62 GHz)
Memory Clock rate: 1100 Mhz
Memory Bus Width: 256-bit
Maximum Texture Dimension Size (x,y,z) 1D=(8192), 2D=(65536, 32768), 3
D=(2048, 2048, 2048)
Maximum Layered 1D Texture Size, (num) layers 1D=(8192), 512 layers
Maximum Layered 2D Texture Size, (num) layers 2D=(8192, 8192), 512 layers
Total amount of constant memory: 65536 bytes
Total amount of shared memory per block: 16384 bytes
Total number of registers available per block: 8192
Warp size: 32
Maximum number of threads per multiprocessor: 768
Maximum number of threads per block: 512
Max dimension size of a thread block (x,y,z): (512, 512, 64)
Max dimension size of a grid size (x,y,z): (65535, 65535, 1)
Maximum memory pitch: 2147483647 bytes
Texture alignment: 256 bytes
Concurrent copy and kernel execution: Yes with 1 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): No
Device PCI Bus ID / PCI location ID: 9 / 0
Compute Mode:
< Default (multiple host threads can use ::cudaSetDevice() with device simu
ltaneously) >

解决方法:

根据this你是对的：

SM =流式多处理器

SP =流处理器= CUDA核心

总SP / CUDA核心数量= SM数量*每个SM的SP / CUDA核心数量

标签：c-3,c,cuda,gpgpu,visual-studio
来源： https://codeday.me/bug/20190825/1718949.html