Hello, I am using the repo you mentioned. I upgraded to latest version and I get the following: versioninfo() Julia Version 0.3.1 Commit c03f413 (2014-09-21 21:30 UTC) Platform Info: System: Linux (x86_64-linux-gnu) CPU: Intel(R) Core(TM) i5-4300U CPU @ 1.90GHz WORD_SIZE: 64 BLAS: libblas.so.3 LAPACK: liblapack.so.3 LIBM: libopenlibm LLVM: libLLVM-3.3
I did not included Julia Dependencies repo because it is meant for Ubuntu up to 13.04. I both repos however OpenBLAS is available only for Raring, Quantal and Precise not for Trusty Tahr ... so I assume Julia 0.3.1~trusty1 is using original Ubuntu repo for linear algebra libraries and thus users of Trusty Tahr ends up without OpenBLAS. Best Regards, Jan Dňa štvrtok, 25. septembra 2014 16:57:48 UTC+2 Andreas Noack napísal(-a): > > It appears that you are not using a fast BLAS. The BLAS and LAPACK entries > in versioninfo() should say libopenblas instead of libblas and liblapack. > You should use > > https://launchpad.net/~staticfloat/+archive/ubuntu/juliareleases > > as your repo for julia. That should give you Julia with fast linear > algebra. > > Med venlig hilsen > > Andreas Noack > > 2014-09-25 10:36 GMT-04:00 Ján Dolinský <[email protected] > <javascript:>>: > >> Hello, >> >> Yes, Andreas point makes sense. Sometimes you may not want threaded >> linear algebra routines. >> >> My current installation reports this: >> versioninfo() >> Julia Version 0.3.0 >> Commit 7681878 (2014-08-20 20:43 UTC) >> Platform Info: >> System: Linux (x86_64-linux-gnu) >> CPU: Intel(R) Core(TM) i5-4300U CPU @ 1.90GHz >> WORD_SIZE: 64 >> BLAS: libblas.so.3 >> LAPACK: liblapack.so.3 >> LIBM: libopenlibm >> LLVM: libLLVM-3.3 >> >> Am I using the right library ? How do I plug-in the OpenBLAS ? I am under >> Ubuntu 14.4.01. >> >> Thanks, >> Jan >> >> Dňa štvrtok, 25. septembra 2014 14:47:12 UTC+2 Andreas Noack napísal(-a): >>> >>> OpenBLAS uses threads by default, but Milan reported that Fedora's >>> maintainer had them disabled. Hence, unless you are using Fedora, you >>> should have threaded OpenBLAS. >>> >>> What is the best setup for fast linear algebra operations ? >>> >>> >>> That question doesn't have a single answer. Often when people want to >>> show performance of linear algebra libraries they run a single routine on a >>> big matrix. In that case you'll often benefit from many threads. However, >>> in many applications you solve smaller problems many times. In this case, >>> many threads can actually be a problem and you could be better off with >>> turning off OpenBLAS threading. So it depends on your problem. >>> >>> Med venlig hilsen >>> >>> Andreas Noack >>> >>> 2014-09-25 5:52 GMT-04:00 Ján Dolinský: >>> >>>> Hello, >>>> >>>> How do I make Julia to use threaded version of OpenBLAS ? Do I have to >>>> compile using some special option or there is a config file ? >>>> What is the best setup for fast linear algebra operations ? >>>> >>>> Best Regards, >>>> Jan >>>> >>>> Dňa nedeľa, 21. septembra 2014 9:50:52 UTC+2 Stephan Buchert >>>> napísal(-a): >>>> >>>>> Wow, I have now LU a little bit faster on the latest julia Fedora >>>>> package than on my locally compiled julia: >>>>> >>>>> julia> versioninfo() >>>>> Julia Version 0.3.0 >>>>> Platform Info: >>>>> System: Linux (x86_64-redhat-linux) >>>>> CPU: Intel(R) Core(TM) i7-4700MQ CPU @ 2.40GHz >>>>> WORD_SIZE: 64 >>>>> BLAS: libopenblas (DYNAMIC_ARCH NO_AFFINITY Haswell) >>>>> LAPACK: libopenblasp.so.0 >>>>> LIBM: libopenlibm >>>>> LLVM: libLLVM-3.3 >>>>> >>>>> julia> include("code/julia/bench.jl") >>>>> LU decomposition, elapsed time: 0.07222901 seconds, was 0.123 seconds >>>>> with my julia >>>>> FFT , elapsed time: 0.248571629 seconds >>>>> >>>>> Thanks for making and improving the Fedora package >>>>> >>>> >>> >
