Andreas,
Ryan,
How did you decide about the Modified Reduction.py that Ryan published
here: http://lists.tiker.net/pipermail/pycuda/2011-June/003196.html
It promises to do exactly what I want, yet I'm not sure it was
committed or can still be applied as a patch to the more recent
release of PyCUDA ReductionKernel. I tried anyway and got compilation
problems from nvcc, identifier "x" is undefined,
maxloc = ReductionKernel(dtype_out=numpy.int32, neutral="0",
reduce_expr="(x[(int)a] > x[(int)b]) ? (int)a : (int)b", map_expr="i",
arguments="float *x")
Igor
On Thu, Nov 17, 2011 at 12:26 PM, Igor <rych...@gmail.com> wrote:
> Alternatively, I could split my struct into the array of the field
> which max() is sought and the array of the remaining fields. But then
> could ReduceKernel be made to return the _position_ and not the value?
> I'd use it to retrieve all the values from the both arrays.
> Igor
>
>
> On Wed, Nov 16, 2011 at 9:38 PM, Igor <rych...@gmail.com> wrote:
>> Either I'm doing something wrong or indeed it's by design that I can't
>> use custom struct-types with ReductionKernel? How do I proceed?
>> Igor
>>
>>
>>
>> Fxy= [('f','double'), ('i', gpuarray.vec.int2)]
>>
>> max = ReductionKernel(dtype_out=Fxy, neutral="0",
>> reduce_expr="max(a.f,b.f)", map_expr="a[i]", arguments="Fxy *x")
>>
>>
>>
>>
>>
>> Traceback (most recent call last):
>> ...
>>
>> File
>> "/usr/local/sage/sage-test/sage-4.7.1/local/lib/python2.6/site-packages/pycuda-2011.1.2-py2.6-linux-x86_64.egg/pycuda/reduction.py",
>> line 187, in __init__
>> dtype_to_ctype(dtype_out), self.block_size,
>> File
>> "/usr/local/sage/sage-test/sage-4.7.1/local/lib/python2.6/site-packages/pycuda-2011.1.2-py2.6-linux-x86_64.egg/pycuda/tools.py",
>> line 399, in dtype_to_ctype
>> raise ValueError, "unable to map dtype '%s'" % dtype
>> ValueError: unable to map dtype '[('f', '<f8'), ('i', [('x', '<u4'),
>> ('y', '<u4')])]'
>>
>
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