728x90
반응형
간단한 예제
import pycuda.autoinit
import pycuda.driver as drv
import numpy
from pycuda.compiler import SourceModule
mod = SourceModule("""
__global__ void multiply_them(float *dest, float *a, float *b)
{
const int i = threadIdx.x;
dest[i] = a[i] * b[i];
}
""")
multiply_them = mod.get_function("multiply_them")
a = numpy.random.randn(400).astype(numpy.float32)
b = numpy.random.randn(400).astype(numpy.float32)
dest = numpy.zeros_like(a)
multiply_them(
drv.Out(dest), drv.In(a), drv.In(b),
block=(400,1,1), grid=(1,1))
print dest-a*b
https://documen.tician.de/pycuda/
Welcome to PyCUDA’s documentation! — PyCUDA 2019.1.1 documentation
Welcome to PyCUDA’s documentation! PyCUDA gives you easy, Pythonic access to Nvidia’s CUDA parallel computation API. Several wrappers of the CUDA API already exist–so why the need for PyCUDA? Object cleanup tied to lifetime of objects. This idiom, often ca
documen.tician.de
728x90
반응형
'AI Development > GPU | CUDA | PyCUDA' 카테고리의 다른 글
[CUDA] CUDA Driver Version (0) | 2020.07.06 |
---|---|
[PyCUDA] 정리중 (0) | 2020.05.14 |
[GPU] GPU Performance 및 Titan V, RTX 2080 Ti Benchmark (0) | 2020.03.04 |
[CUDA] CUDA Capability 확인 (2) | 2019.05.31 |
[CUDA] Visual Studio 2015, OpenCV , CUDA 연동하기 (3) | 2017.01.25 |