Dear Andreas, dear all,
thank you very much! I will install this package and perform the sample
code! I hope after that you can correct me.
Best regards,
Evgeny
Am 23.02.2014 04:31, schrieb Andreas Kloeckner:
Evgeny Lazutkin <[email protected]> writes:
Dear all!
I need your help! First of all, let me please introduce myself. My name
is Evgeny and currently I am scientific researcher at the university in
Germany.
I am working with optimization of the large scale system. Based on the
algorithm, I have realized that I can use parallel programming with GPU.
The programming language is Python, but I found in Internet, that I can
use pyCUDA to solve my problem.
The major time consumption in my program is to solve huge linear
equation system in the form *A*X = B*, where *X* and *B* are matrices.
The main idea is to divide the matrices (it is possible due to the
algorithm and structure) and to obtain the acceleration of the
calculation. Unfortunately, I cannot understand how to realize this
under pyCUDA.*Could you please provide the example: how to solve such
the system within pyCUDA?*
I have mentioned, that there is "CUDA SciKit" [1], which provides
Python interfaces to a subset of the functions in the CUDA, CUDART,
CUBLAS, and CUFFT libraries distributed as part of NVIDIA's CUDA
Programming Toolkit, as well as interfaces to select functions
in the basic and premium versions of the CULA Toolkit. Is it a correct
way? Or did I make a mistake? Probably you have a better solution? But I
still need an example.
Here are two starting points:
http://lebedov.github.io/scikits.cuda/generated/scikits.cuda.linalg.cho_factor.html
(That's Cholesky, you want LU.)
http://lebedov.github.io/scikits.cuda/generated/scikits.cuda.cula.culaDeviceDgetrf.html#scikits.cuda.cula.culaDeviceDgetrf
(This performs LU.)
HTH,
Andreas
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