On Saturday, March 14, 2015 at 5:26:25 PM UTC, Erik Schnetter wrote: > As long as linear algebra is handled by BLAS, using multi-threading in > Julia isn't really necessary. If the matrices are large enough to warrant > multithreading, then using a multi-threaded BLAS is usually more > efficient... >
Obviously, not everything one might need to do with a matrix is a BLAS operation. In my line of work, the computation time split between BLAS calls (gemm) and scalar math operations. If BLAS is nicely parallelized across 16 CPUs, but the other operations are single-threaded, then those scalar operations are going to become the bottleneck. > > -erik > > On Mar 13, 2015, at 16:54 , Tobias Knopp <tobias...@googlemail.com > <javascript:>> wrote: > > > > you can start with a simple matrix-vector or matrix-matrix product. > imfilter (Images.jl) is also a function that can benefit from > multithreading. > > > > Am Freitag, 13. März 2015 04:52:37 UTC+1 schrieb Viral Shah: > > I am looking to put together a set of use cases for our multi-threading > capabilities - mainly to push forward as well as a showcase. I am thinking > of starting with stuff in the microbenchmarks and the shootout > implementations that are already in test/perf. > > > > I am looking for other ideas that would be of interest. If there is real > interest, we can collect all of these in a repo in JuliaParallel. > > -- > Erik Schnetter <schn...@gmail.com <javascript:>> > http://www.perimeterinstitute.ca/personal/eschnetter/ > > My email is as private as my paper mail. I therefore support encrypting > and signing email messages. Get my PGP key from https://sks-keyservers.net. > > >
