[Beowulf] A simple cluster
Joe Landman
landman at scalableinformatics.com
Fri Jun 27 09:42:23 PDT 2008
Peter St. John wrote:
> I recall discussion of the hybrid approach, which I think most of the
> list doesn't much like, but interested me on account of my application.
> But I hadn't realized that hybrid was required by OpenMP for multi node
OpenMP is shared memory. You can "fake" shared memory using a variety
of techniques (Intel Cluster OpenMP does some of this). You can create
a real distributed shared memory using ScaleMP tools. But at the end of
the day, the OpenMP spec assumes that each thread has equal access to
all of the (global) data. Yes, there are thread private bits, and with
some work you may be able to get the access to global data with some
sort of abstraction layer (e.g. not-cheap-in-time).
> architectures. So yeah, I'll just go with MPI for starters. When I start :-)
> Peter
MPI isn't perfect, but mixing multiple models together doesn't make it
any easier to program (somewhat harder).
It might be worth noting that the advancing of many-cores are upon us,
so that all your nodes will look like "large" SMPs with a memory
hierarchy and a bandwidth wall. With accelerators they will look like
asymmetric multi processors (aSMP), often with differing ABIs. Lots of
ways you can program those as well.
We live in interesting times :)
>
> On 6/26/08, *Geoff Jacobs* <gdjacobs at gmail.com
> <mailto:gdjacobs at gmail.com>> wrote:
>
> Peter St. John wrote:
> > Geoff,
> > Oops! I totally misunderstood it. So it's strictly shared-memory, and
> > requires something like MPI for crossing nodes. Gotcha. Big
> mistake, thanks.
> > Peter
>
>
> Shared memory only, yes. Many, many people skip OpenMP completely and go
> pure MPI. From a coding standpoint it's far easier to multiprocess using
> one technique rather than two, and the performance gains for using both
> tend to be marginal or non-existent -- at least in my experience.
>
> There was a long discussion a while back on the list about the pros and
> cons of each approach.
>
>
>
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--
Joseph Landman, Ph.D
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Scalable Informatics LLC,
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