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Dear All,
I have one inversion matrix routine for complex non-symmetric and full matrix, based on Gauss-Jordan algorithm and written in Fortran 95. For large matrix (> 2500 x 2500) it takes a lot of time, thus I would like to use parallel or multithreading computation. There so many solution on the market: OpenMP, MPI, multithreading, MultiCore, GPU (it seemed to be fast)... Can someone tell me what is the best portable solution.
Best regards,
Didace
I have one inversion matrix routine for complex non-symmetric and full matrix, based on Gauss-Jordan algorithm and written in Fortran 95. For large matrix (> 2500 x 2500) it takes a lot of time, thus I would like to use parallel or multithreading computation. There so many solution on the market: OpenMP, MPI, multithreading, MultiCore, GPU (it seemed to be fast)... Can someone tell me what is the best portable solution.
Best regards,
Didace
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No, as you don't care to tell why you are doing this, no one will be able to tell you what is best. Are you not aware that libraries such as MKL and ACML support pre-built OpenMP methods?
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Quoting - tim18
No, as you don't care to tell why you are doing this, no one will be able to tell you what is best. Are you not aware that libraries such as MKL and ACML support pre-built OpenMP methods?
Thank you very much for your answer. I have try MKL, but I was not able to make it run and I don't know if it yes portable. I mean by protable, if I can compile and linke an executable and send it to someone else for use !
Best regards,
Didace
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If all you are looking for is portability, then your problem lies not in the threading API / library, bur rather in the language. For good portability, try to implement it in Java.

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