Hi all, On Mon, 16 Jan 2012 20:11:59 -0500, Andreas Kloeckner <[email protected]> wrote: > Here's what I think is a bug in the Nvidia CL implementation. The > assertion fails on my GTX 260, but is fine just about anywhere else. > > 8< -------------------------------------------------------- > #! /usr/bin/env python > > import pyopencl as cl > import pyopencl.array > import numpy as np > > > ctx = cl.create_some_context() > queue = cl.CommandQueue(ctx) > > n = 2**20 + 1 > dtype = np.int32 > host_data = np.random.randint(0, 10, n).astype(dtype) > dev_data = cl.array.to_device(queue, host_data) > host_data_2 = dev_data.get() > > assert (host_data == host_data_2).all() > 8< -------------------------------------------------------- > > Yes, you read that right--it seems they messed up just transferring a > bit of memory. As is to be expected, the bug is very sensitive to the > size (n). > > Infuriatingly, this happened in the unit test for parallel scan, so for > a very long time I hunted for a scan bug that didn't exist. :( > > I hope I'm not crazy. In any case, I thought this might be important > enough to warn you guys about. Happens for me with 290.x and 295.x > drivers on a GTX260. No problem on Fermi.
If there's anyone with a GTX260 (Core 216) out there, I'd be much obliged if you could try the script above and report if it gives an AssertionError or not. So far, my desktop is the only machine on which the bug seems reproducible. Thanks a lot, Andreas
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