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')])]' _______________________________________________ PyCUDA mailing list PyCUDA@tiker.net http://lists.tiker.net/listinfo/pycuda