[Trilinos-Users] Trilinos-Users Digest, Vol 102, Issue 8

Bartlett, Roscoe A. bartlettra at ornl.gov
Mon Feb 17 12:40:29 MST 2014

If you have the Intel MKL and use that for the BLAS and LAPACK TPLs, I think you get this already do you not?



> -----Original Message-----
> From: trilinos-users-bounces at software.sandia.gov [mailto:trilinos-users-
> bounces at software.sandia.gov] On Behalf Of Hoemmen, Mark
> Sent: Monday, February 17, 2014 2:33 PM
> To: trilinos-users at software.sandia.gov
> Subject: Re: [Trilinos-Users] Trilinos-Users Digest, Vol 102, Issue 8
> Hi Chen -- The best thing for you to do would be to give the Teuchos dense
> matrix to a shared-memory parallel BLAS / LAPACK implementation, or to a
> library such as PLASMA or MAGMA.  If I recall correctly, at least PLASMA if
> not also MAGMA has parallel algorithms that would help with your problem.
> It's not Kokkos' job to implement dense matrix factorizations; other libraries
> do a great job with that.
> Thanks!
> mfh
> ________________________________________
> Message: 1
> Date: Mon, 17 Feb 2014 11:53:32 +0900
> From: ChenYurui <tin at mma.cs.tsukuba.ac.jp>
> Subject: [Trilinos-Users] Use shared memory in Teuchos dense matrix
> To: trilinos-users <trilinos-users at software.sandia.gov>
> Message-ID: <530179AC.1050604 at mma.cs.tsukuba.ac.jp>
> Content-Type: text/plain; charset=ISO-2022-JP
> Hi everyone,
> There is some reasons that I have to use a Teuchos dense matrix and
> Teuchos lapack to compute orthonormal basis matrix. Due to size of that
> matrix is somehow so big, I wonder that if shared memory can be applied
> into the computation process to speed up. I only know that Kokkos can
> deal with this problem, however it seems that the matrix must be a
> Tpetra matrix.
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