[Beowulf] CCL:Question regarding Mac G5 performance (fwd from mmccallum at pacific.edu)

Michael Huntingdon hunting at ix.netcom.com
Thu May 20 17:26:13 PDT 2004

At 01:23 PM 5/20/2004, Joe Landman wrote:
>On Thu, 2004-05-20 at 02:05, Michael Huntingdon wrote:
> > I've spent some time sifting through the attached numbers. Though not each
>Any paper that starts out praising spec as a "good" predictive benchmark
>is suspect.  Benchmarking is difficult to do right, in large part
>because of deceptively simple scoring functions (time, frequency (not of
>the CPU, but number of iterations per unit time), ...).
Although SPEC was included among others, I didn't see where Martyn Guest 
"praised" SPEC.

>Further, looking these over, I did not see much of a discussion (though
>it is implied by the use of certain compilers) of the effects of things
>like SSE2 in the P4, memory alignment, 32/64 bit
>compilation/optimization, use of tuned libraries where available...
>Given the sheer number of machines tested, it is unlikely that they used
>up to date compilers (latest gcc's are better than earlier gcc's for
>performance), or recompiled the binary for all the different platforms
>to run native.  The ifc results seem to indicate that they used SSE2 on
>P4's but probably used plain old 32 bit code on Opterons.

I wouldn't begin to speculate; however, would hope Daresbury Laboratory and 
Martyn Guest were working to advance research, using the best technology 
available for each platform. I didn't see anything in their mission 
statement which leads me to think otherwise.

> > lends itself to hp Itanium 2, there appears to be a very balanced trend.
>... in a specific set of operations relevant for specific classes of

The tables cover a wide range of benchmarks specific to the interests of 
those working in computational chemistry. With respect to this, the rx2600 
(Itanium 2 based) ranked among the top ten (with the exception of table 4 
where it was ranked #11). Averaged out, the tables reflect an overall 
rating of 5.86 among the 400 platforms tested. My initial conclusion may 
have been less than scientific, but I'll stay with it for now.

>Not everyone in HPC does matrix work, eigenvalue extraction, etc.  Some
>of us do things like string/db searching (informatics).  There, the
>numbers look quite different.

My comments referenced numerically intensive research rather than I/O 
intensive environments. I'm surprised 8GB of memory is enough to sustain 
superior performance when searching very large data sets normally 
associated with bio-informatics.


>[... snip ...]
>Joseph Landman, Ph.D
>Scalable Informatics LLC,
>email: landman at scalableinformatics.com
>web  : http://scalableinformatics.com
>phone: +1 734 612 4615

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