【NVIDIA讲座】CUDA Python

CUDA
compute Unified Device Architecture

CUDA C/C++
基于C/C++的编程方法
支持异构编程的扩展方法
简单明了的API

CUDA支持的编程语言:
C/C++/PYTHON/Fortran/Java/...

CUDA并行计算模式
并行计算是同时应用多个计算资源解决一个计算问题
(空间换时间)

异构计算
HOST CPU和内存(host memory)
DEVICE GPU和现存 (device memory)




32个CUDA核(一个warp)共享一个execution contexts

CUDA Python

host: The CPU
device: The GPU
host memory: The system main memory
device memory: Onboard memroy on a GPU card
kernals: a GPU function launched by the host and executed on the device
device function: a GPU function executed on the device which can only be called from the device (i.e. form a kernel or another device function)

定义Kernal函数:

@cuda.jit('void(int32[:]),int32[:]')
def foo(aryA,aryB):
      ...

调用Kernal函数:

griddim = 1,2
blockdim = 3,4
foo[griddim,blockdim](aryA,aryB)

查看CUDA 版本

nvcc -V

创建文件

touch 20200609-python-cuda-cv.py
posted @ 2020-06-29 13:54  Maxwell'Maxwill  阅读(590)  评论(0编辑  收藏  举报