I am currently using pycuda and scikits.cuda to solve linear equation A*x = b, where A is an upper/lower matrix. However the cublasStbsv routine requires a specific format. To give an example: if a lower matrix A = [[1, 0, 0], [2, 3, 0], [4, 5, 6]], then the input required by cublasStbsv should be [[1, 3, 6], [2, 5, 0], [4, 0, 0]], where rows are diagonal, subdiagonal1, subdiagonal2, respectively. If using numpy, this can be easily done by stride_tricks.as_strided, but I dont know how to do similar things with pycuda.gpuarray. Any help would be appreciated, thanks. I found pycuda.compyte.array.as_strided, but it cannot be applied to gpuarray.
How to convert an upper/lower gpuarray to the specific format required by cublasStbsv?
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I got it done by using theano. First converted it to cudandarray, change stride and make a copy back to gpuarray. Just be careful about changes between Fortran and C order. update: finally got it done by using gpuarray.multi_take_put