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2015-06-03 20:45 344 查看

Easy OpenCL with Python

原文 http://www.drdobbs.com/open-source/easy-opencl-with-python/240162614

OpenCL与python联合工作:与CUDA的前景分析

http://www.opengpu.org/forum.php?mod=viewthread&tid=16571

如果你对python熟,可以用 PyOpenCL, 兼顾 host 端的简洁与 device 端的高效。
kernel 函数可以写在单独的 *.cl 文件里, 一句 python 命令就可以 load + build:
prg_src = open( 'kernel_test1.cl', 'r').read()
prg = cl.Program(ctx, prg_src).build()

#!/usr/bin/env python

import numpy as np
import pyopencl as cl

a_np = np.random.rand(50000).astype(np.float32)
b_np = np.random.rand(50000).astype(np.float32)

ctx = cl.create_some_context()
queue = cl.CommandQueue(ctx)

mf =  cl.mem_flags
a_g = cl.Buffer(ctx, mf.READ_ONLY | mf.COPY_HOST_PTR, hostbuf=a_np)
b_g = cl.Buffer(ctx, mf.READ_ONLY | mf.COPY_HOST_PTR, hostbuf=b_np)

prg = cl.Program(ctx, """
__kernel void sum(__global const float *a_g,
__global const float *b_g,
__global float *res_g)
{
int gid = get_global_id(0);
res_g[gid] = a_g[gid] + b_g[gid];
}
""").build()

res_g = cl.Buffer(ctx, mf.WRITE_ONLY, a_np.nbytes)
prg.sum(queue, a_np.shape, None, a_g, b_g, res_g)

res_np = np.empty_like(a_np)
cl.enqueue_copy(queue, res_np, res_g)

# Check on CPU with Numpy:
print(res_np - (a_np + b_np))
print(np.linalg.norm(res_np - (a_np + b_np)))


GPGPU OpenCL/CUDA 高性能编程的10大注意事项

http://www.cnblogs.com/xudong-bupt/p/3630952.html

从零开始学习OpenCL开发(一)架构

http://blog.csdn.net/leonwei/article/details/8880012

在Android上使用OpenCL调用GPU加速

http://blog.csdn.net/dj0379/article/details/39484061
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