MAGMA Forum

Thanks for your input. We'll keep it in mind for future developments.
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SLATE is a good choice for a distributed solver with CPUs or CPUs + GPUs. For using CPUs + GPUs, it would require that the distributed matrix fits in the cumulative memory of all the GPUs. For a single node, MAGMA will also do out-of-GPU-memory algorithms for such large matrices. Just call magma_dge...

You can name mangle the functions in magma/testing/lin/
In magma/testing/Makefile.sr, see variable liblapacktest_src for the 36 or so files that are used. The other files in that directory were copied from LAPACK but aren't used.

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[sdcz]qpt01 are LAPACK testing functions. They would not be in the LAPACK library, per se, but in LAPACK's testing. MAGMA has its own copy of them: >> pfind -i qpt01 lapack lapack/TESTING/LIN/cqpt01.f lapack/TESTING/LIN/dqpt01.f lapack/TESTING/LIN/sqpt01.f lapack/TESTING/LIN/zqpt01.f >> pfind -i qpt...

magma_cgesv works on multiple GPUs; it calls magma_cgetrf, which calls magma_cgetrf_m. However, as you observe, the forward and back solves (getrs) are on the CPU. It's unclear if multi-GPU pivoting (laswp) and triangular solves (trsm) in getrs would benefit from the GPU, since there would be signif...

Yes, magma_dmalloc is just a wrapper around cudaMalloc. It is type-safe (you don't need to use sizeof(double) as you do with cudaMalloc), but otherwise nothing special going on. If you call asynchronous MAGMA routines that take a magma_queue, use the stream from the magma_queue to call CUDA function...

I'm not sure what you mean by "the arrays created by MAGMA routines". Do you mean arrays allocated by, say, magma_dmalloc? Yes, that's just a chunk of memory on the GPU, so you can process it equally well with MAGMA, cuBLAS, and your own custom CUDA kernels. It sounds like checking the coefficients ...

You need to have a Bitbucket account to post bug reports. I posted this there for tracking:
https://bitbucket.org/icl/magma/issues/ ... es-nans-on

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Use magma_dgemm. It is simply a wrapper around cublasDgemm. magmablas_dgemm is MAGMA's own implementation, which dates back to the Fermi architecture. NVIDIA adapted this implementation for the cublasDgemm, and further optimized it. We keep the code around in case someone wants an open-source implem...

I think you are on the wrong forum. This forum is for MAGMA, the GPU library for linear algebra (http://icl.utk.edu/magma/). It sounds like you want MAGMA, the computational algebra system (http://magma.maths.usyd.edu.au/magma/).
-mark