1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
|
from __future__ import absolute_import
from __future__ import print_function
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import numpy as np
import pyopencl as cl
import pyopencl.array
from pyopencl.elementwise import ElementwiseKernel
n = 10
a_np = np.random.randn(n).astype(np.float32)
b_np = np.random.randn(n).astype(np.float32)
ctx = cl.create_some_context()
queue = cl.CommandQueue(ctx)
a_g = cl.array.to_device(queue, a_np)
b_g = cl.array.to_device(queue, b_np)
lin_comb = ElementwiseKernel(ctx,
"float k1, float *a_g, float k2, float *b_g, float *res_g",
"res_g[i] = k1 * a_g[i] + k2 * b_g[i]",
"lin_comb"
)
res_g = cl.array.empty_like(a_g)
lin_comb(2, a_g, 3, b_g, res_g)
# Check on GPU with PyOpenCL Array:
print((res_g - (2 * a_g + 3 * b_g)).get())
# Check on CPU with Numpy:
res_np = res_g.get()
print(res_np - (2 * a_np + 3 * b_np))
print(np.linalg.norm(res_np - (2 * a_np + 3 * b_np)))
|
