Consider the following code:
import numpy
import pyopencl as cl
import pyopencl.array as array
def to_device(ctx, queue, arr):
size = arr.size * arr.dtype.itemsize
buf = cl.Buffer(ctx, cl.mem_flags.READ_WRITE, size=size)
arr_dev = array.Array(queue, arr.shape, arr.dtype, data=buf)
arr_dev.set(arr, queue=queue, async_=True)
return arr_dev
ctx = cl.create_some_context()
queue = cl.CommandQueue(ctx)
a = numpy.empty(1024 * 4000, numpy.uint64)
ad = to_device(ctx, queue, a)
b = numpy.empty(1024 * 4000, numpy.int32)
bd = to_device(ctx, queue, b)
c = numpy.empty(1024 * 32, numpy.int32)
cd = to_device(ctx, queue, c)
# queue.finish() # uncommenting this line fixes the problem
ad.get()
When I run it on Linux, Tesla P100 and using CUDA as the OpenCL platform,
most of the time (not always) the execution hangs on the last line. Does
anyone have any ideas about what might be happening here?
(If I just use array.to_device(), the problem disappears. This is an
extract from a larger code, where a separate creation of the buffer is
necessary)
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