root / ETSN / MySteps.py @ 272
Historique | Voir | Annoter | Télécharger (957 octet)
1 |
#!/usr/bin/env python3
|
---|---|
2 |
|
3 |
import numpy as np |
4 |
import pyopencl as cl |
5 |
|
6 |
a_np = np.random.rand(50000).astype(np.float32)
|
7 |
b_np = np.random.rand(50000).astype(np.float32)
|
8 |
|
9 |
ctx = cl.create_some_context() |
10 |
queue = cl.CommandQueue(ctx) |
11 |
|
12 |
mf = cl.mem_flags |
13 |
a_g = cl.Buffer(ctx, mf.READ_ONLY | mf.COPY_HOST_PTR, hostbuf=a_np) |
14 |
b_g = cl.Buffer(ctx, mf.READ_ONLY | mf.COPY_HOST_PTR, hostbuf=b_np) |
15 |
|
16 |
prg = cl.Program(ctx, """
|
17 |
__kernel void sum(
|
18 |
__global const float *a_g, __global const float *b_g, __global float *res_g)
|
19 |
{
|
20 |
int gid = get_global_id(0);
|
21 |
res_g[gid] = a_g[gid] + b_g[gid];
|
22 |
}
|
23 |
""").build()
|
24 |
|
25 |
res_g = cl.Buffer(ctx, mf.WRITE_ONLY, a_np.nbytes) |
26 |
knl = prg.sum # Use this Kernel object for repeated calls
|
27 |
knl(queue, a_np.shape, None, a_g, b_g, res_g)
|
28 |
|
29 |
res_np = np.empty_like(a_np) |
30 |
cl.enqueue_copy(queue, res_np, res_g) |
31 |
|
32 |
# Check on CPU with Numpy:
|
33 |
print(res_np - (a_np + b_np)) |
34 |
print(np.linalg.norm(res_np - (a_np + b_np))) |
35 |
assert np.allclose(res_np, a_np + b_np)
|