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On 6/26/10 12:15 PM, Edward Ned Harvey wrote:
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<p class="MsoNormal">Apparently, physicalization is the reverse of
virtualization. The use of hundreds of low-power (like atom, arm, etc)
processors each running its own OS, instead of a smaller number of
higher-power
(like xeon, etc) processors ... To build-out highly parallelized
servers, for
the purpose of either eliminating the need for virtualization, or to
run highly
parallelized and distributed work loads supposedly cheaper and less
power hungry
than the equivalent high-power "standard" server solution...<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">I am aware of products from seamicro and
rackable
(sgi). Does anybody have any experience in this area? Know any
other options I should consider?<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">The specific requirement we're solving is a
workload which
is highly parallelizable. We're currently paying Amazon EC2, but
finding
it's not very economical. So we're exploring alternatives, hoping to
find
a way to run these parallelized jobs more economically. It is also
ideal
to keep the workload in-house, so we can eliminate the security concern
about
Amazon employees having access to our data and so forth.<o:p></o:p></p>
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<br>
Keep us updated on what you discover on this front. People have been
trying this kind of thing in different forms for quite awhile.<br>
<br>
We have some highly parallelizable workloads, but are in an academic
research environment and can benefit from the US Open Science Grid from
which we have (recently) been able to secure sustained access to 3000+
job slots at computing centers across the US in an "opportunistic" mode
which means we use otherwise idle compute cycles at non-commercial
research institutions (some federal, some state, some universities).<br>
<br>
If I were you, I'd look into the 4x12 core AMD systems. These things
are half price or less on similar Nehalem Xeon systems on a per-core
basis, but you then have to figure out if you are OK with the memory,
disk, network I/O patterns and can live with the slower AMD processors.<br>
<br>
>From a different perspective, (and also *very* dependent on your having
a good grasp of the workload characteristics), if this is a high value
and long term workload you *may* be able to benefit from GPUs, which
effectively are hundreds of slower compute cores accessible from the
same system image, but will require a small computational kernel which
you can port to a GPU environment.<br>
<br>
Ian<br>
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