Hi Nicholas, On Samstag 28 Februar 2009, Nicholas Tung wrote: > In much of the tutorial, numpy arrays are treated as buffer objects.
In the implementation, too. In particular, memcpy_htod doesn't really care what it's given, as long as that something adheres to the Python buffer interface. Numpy arrays do so most of the time. > This doesn't always work, and should be pointed out somewhere... What's the failure? If it's something non-intuitive, we should catch it in PyCuda and give a nicer warning. > I found > out the hard way. I don't know if compressed matrices have the similar > effects, but this code seems to fail for me. > > new = numpy.concatenate([original, numpy.zeros((original.shape[0], 0), > uint32)], axis=1) > gpu = drv.to_device(new.astype(uint32)) > > The ndarray.copy function seems to resolve the problem. Sorry I'm not > familiar with numpy internals. Please post the output of print original.shape print original.strides print original.flags Andreas PS: Please use the mailing list for all questions, for archival mainly.
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