And https://github.com/JuliaLang/julia/issues/16729
On Friday, August 12, 2016 at 7:43:56 PM UTC+2, Kristoffer Carlsson wrote: > > Ref https://github.com/JuliaLang/julia/pull/17429 > > On Friday, August 12, 2016 at 7:39:40 PM UTC+2, Doan Thanh Nam wrote: >> >> Hi, >> >> I am new to Julia Language and I am curious to use it for my work. >> Recently, I have tried to use it for some of my projects and observed some >> interesting cases. >> >> First of all, when I start Julia REPL without adding any worker processes >> and do matrix multiplication. Julia takes all CPU cores in my computer to >> speed up the computation. I guess it used OpenBLAS. The code is >> X = randn(5000, 5000); Y = randn(5000, 5000); X * Y; >> >> >> However, after adding some worker processes by using *addprocs*(4) and >> do matrix multiplication. It runs the computation on only 1 CPU core and it >> slows down my performance. Even if I remove all worker processes that I add >> and run the multiplication again, it still uses one CPU core to do. The >> code is >> addprocs(4); X = randn(5000, 5000); Y = randn(5000, 5000); X * Y; >> rmprocs(2); rmprocs(3); rmprocs(4);rmprocs(5);X = randn(5000, 5000); Y = >> randn(5000, 5000); X * Y; >> >> >> My question here is that: Are there any ways to use all cores to do >> matrix multiplication ( and other matrix methods) with multiple cores after >> *addprocs*()? >> >> Thanks. >> >
