Re: [eigen] benchmarks for large matrices? |

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*To*: eigen@xxxxxxxxxxxxxxxxxxx*Subject*: Re: [eigen] benchmarks for large matrices?*From*: Benoit Jacob <jacob.benoit.1@xxxxxxxxx>*Date*: Tue, 17 Feb 2009 21:40:12 -0500*Dkim-signature*: v=1; a=rsa-sha256; c=relaxed/relaxed; d=gmail.com; s=gamma; h=domainkey-signature:mime-version:received:in-reply-to:references :date:message-id:subject:from:to:content-type :content-transfer-encoding; bh=1xvhGQqcn59Kb3EBj0lKWJQzSCIBUj9QFMxB8OTDEmA=; b=rblLyzFD91+cEQQZz0hfBn3fF1bnbtzUPvVZK49TVdl8Nm2ab6Wf9xO+DjGOAKgDKE +hkAPX5xo5LVtjJ2NqfzOo0NHk1ZUG4ABMGwm1K3nEdtd0eKKix7VYmfDZu1UD4qO0+B /ye3bwaKg9rQEXuy64yR/FvKxrGtDKEZv/Hf8=*Domainkey-signature*: a=rsa-sha1; c=nofws; d=gmail.com; s=gamma; h=mime-version:in-reply-to:references:date:message-id:subject:from:to :content-type:content-transfer-encoding; b=cyWy84ab00XfInNYc4oysgoWkvV9x0sXDq2HiDsspDgHhlk03fFnIWmk31fg9sM5bM iTk/DlIJ31+S+Oby1dyl8+a/OY+AKJejBDKJODxXyeCy9XosGsuHt/pFovLKPVgLgs9j GgYL6flCfftOxHwufggLKqKhsK8ijHuPBJ95A=

2009/2/17 David Roundy <daveroundy@xxxxxxxxx>: > Hello eigen folks, > > I recently took a look at the very impressive benchmarks shown at: > > http://eigen.tuxfamily.org/index.php?title=Benchmark > > and had a couple of questions. First, would it be a problem to extend these > benchmarks to larger matrices? A user benchmarked 4000x4000 matrix products against MKL: http://forum.kde.org/solved-newbie-speed-on-dense-matrix-t-20846.html His result was the same that we got in our benchmark for 1000x1000: Namely, Eigen is at about 2/3 of the speed of MKL. > multiplication of two (21,000 by 100) matrices (I just took these numbers > from a recent calculation), multiplied such that the result is a small, > square matrix. Ah, we dont have benchmarks for that. > Relating to that, I was curious as to the options given to ATLAS. If it's > running without sse2 support compiled in, then it should be compared with > eigen2_novec, and is quite competitive and sometimes wins. However, if it > was compiled with sse2 support, then eigen2 appears much more impressive. I cant speak for Gael who did all the benchmarking (as well as all the optimization of matrix products), but, as written on this benchmark page, his architecture is x86-64, and on this architecture SSE2 is enabled by default (because all x86-64 cpus support SSE2). So I would be very surprised if his ATLAS didn't use SSE2. Thanks for your interest, Benoit

**Follow-Ups**:**Re: [eigen] benchmarks for large matrices?***From:*Gael Guennebaud

**References**:**[eigen] benchmarks for large matrices?***From:*David Roundy

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