Fortran vs. Matlab on linear algebra

#21 08-12-2008, 05:46 PM

Gib Bogle <bogle@ihug.too.much.spam.co.nz> wrote:

> The reason I did this
> quick test is that I have a student who is solving a nonlinear system of
> PDEs

Why on earth do you then benchmark with a matrix-matrix multiplly?
Operations on PDEs (which I assume are all sparse matrices) can not be
more unlike a mmm. You should have benchmarked the sparse matrix vector
product, and you would actually see that matlab was much slower since
its sparse data format is really inefficient.

Victor.
--
Victor Eijkhout -- eijkhout at tacc utexas edu

#22 08-21-2008, 01:22 PM

On Aug 12, 2:46*pm, s...@sig.for.address (Victor Eijkhout) wrote:
> Gib Bogle <bo...@ihug.too.much.spam.co.nz> wrote:
> > The reason I did this
> > quick test is that I have a student who is solving a nonlinear system of
> > PDEs
>
> Why on earth do you then benchmark with a matrix-matrix multiplly?
> Operations on PDEs (which I assume are all sparse matrices) can not be
> more unlike a mmm. You should have benchmarked the sparse matrix vector
> product, and you would actually see that matlab was much slower since
> its sparse data format is really inefficient.
>
> Victor.
> --
> Victor Eijkhout -- eijkhout at tacc utexas edu

Imagine my surprise in seeing your name on this newsgroup. But then
knowing your profession, it makes sense.

Chris Brown

#23 09-05-2008, 02:39 AM

On 7 Aug, 14:35, none <n...@none.net> wrote:
> On Thu, 07 Aug 2008 07:11:30 -0700, rusi_pathan wrote:
> > On Aug 7, 3:43 am, Gib Bogle <bo...@ihug.too.much.spam.co.nz> wrote:
> >> Fly Away wrote:
> >> > Last time I played with Matlab (about a year ago), it already had an
> >> > option to use multithreading (SMP). It was not enabled by default
> >> > though. Could it be that in your case Matlab had this option enabled?
> >> > That would explain such a dramatic difference.
> >> > Also, I would recommend Goto BLAS or ATLAS as a free alternative to
> >> > INTEL MKL.
>
> >> I checked, that timing is with no multithreading. *It goes faster when
> >> more than one CPU is used, although 4 is slightly slower than 3 - a
> >> common result on the quad core, I've observed. *Memory bus congestion
> >> and/or cache contention is the cause, apparently.
> > Are you using an Intel machine? Seems like Matlab (7.01 and above)
> > also use the MKL underneath:
>
> >http://www.mathworks.com/support/sol....html?solution...
>
> > "In MATLAB 7.0.1 (R14SP1) on computers that use Intel processors, the
> > default BLAS library is the Math Kernel Library (MKL) BLAS provided by
> > Intel."
>
> > That may explain why matmul was slower? With Fortran it is always a
> > good idea to use the vendor supplied/tuned blas/lapack (MKL for Intel,
> > ACML for AMD, Sunperf for Sun and so on). The implementations of
> > matmul may not always be highly optimized though there is little
> > excuse for not doing it.
>
> > Moreover using blas in MKL is also very simple, specially with the
> > Fortran 95 wrappers that come along with it. For example
> > "C=matmul(A,B)" is easily replaced by "call gemm(A,B,C)"
>
> Sadly the MKL is sold separately, rather than bundled into Intel's
> Fortran. There was a time when it was a free download, but that was many
> years ago. We just have to accept that Intel wish to hobble their compiler
> to sell us additional products.- Hide quoted text -
>
> - Show quoted text -

Actually, MKL IS bundled with Intel's Fortran Compiler, and C++
Compiler, and Fortran/C++ Compiler Suite, and Cluster Toolkit. As
well as available standalone, including free for non-commericial use.

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