Re: results from tuning LAPACK

>On Sun, 2008-08-10 at 07:50 -0500, Clint Whaley wrote:
>> Guys,
>>
>> My paper on the benefits of empirically tuning LAPACK's
>>ILAENV-controlled NB
>> has been accepted for CANA'08.  You can see a draft of it at:
>>    http://www.cs.utsa.edu/~whaley/papers/lanb.pdf
>>
>> It shows the advantage you get from tuning NB for several different
>>BLAS
>> an a couple of platforms.  Depending on problem size and
>>architecture,
>> you can be leaving as much as 30% (or 75%, if on the Itanium :) on
>>the table
>> if you use stock lapack's ILAENV.  It also highlights two new tools
>>available
>> in ATLAS (lapack timer/tuner and a tool that takes ATLAS timer
>>output,
>> does some simple statistics, and prints it out in a spreadsheet
>>friendly
>> format).
>>
>> We can apply this tuning to pretty much any blocked LAPACK routine.
>> ATLAS
>> presently handles tuning the factorizations.  My guess is that the
>>next
>> most important routines are the eigencodes.  Does anyone want to
>>nominate
>> particular routines that they use a lot?
>
>Real symmetric eigensolvers are a big workhorse in lots of areas ...
>even undergraduate chemistry. :)

> Singular Value Decomposition is
>another
>workhorse -- gotta have it.
>
>Question -- is anybody putting this much effort into tuning *sparse*
>linear algebra? Something approaching ATLAS performance on huge
>sparse
>matrix-vector multiplies would give significant improvements in many
>areas, including my personal favorite, Markov chains.
>>
>> Cheers,
>> Clint
>>
>> **************************************************************************
>> ** R. Clint Whaley, PhD ** Assist Prof, UTSA **
>>www.cs.utsa.edu/~whaley **
>> **************************************************************************
>>
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>--
>M. Edward (Ed) Borasky
>ruby-perspectives.blogspot.com
>
>"A mathematician is a machine for turning coffee into theorems." --
>Alfréd Rényi via Paul Erdős
>
>
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