update with example gpu

test_gpu.py

+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)
+knl = prg.sum  # Use this Kernel object for repeated calls
+knl(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)))
+assert np.allclose(res_np, a_np + b_np)