[Beowulf] RE: programming multicore clusters
richard.walsh at comcast.net
richard.walsh at comcast.net
Sat Jun 16 06:44:10 PDT 2007
From: Joe Landman <landman at scalableinformatics.com>
> Greg Lindahl wrote:
> > On Fri, Jun 15, 2007 at 09:57:08AM -0400, Joe Landman wrote:
> >> First, shared memory is nice and simple as a programming model.
> > Uhuh. You know, there are some studies going where students learning
> > parallel programming do the same algorithm with MPI and with shared
> > memory. Would you like to make a bet as to whether they found shared
> > memory much easier?
> I don't know which "studies" you are referring to. Having taught
> multiple graduate level courses on MPI/OpenMP programming, I can tell
> you what I observed from my students. They largely just "get" OpenMP.
> It won't get them great overall performance, as there aren't many large
> multiprocessor SMPs around for them to work on. Be that as it may, they
> had little problem developing good code. Compare this to MPI, and these
> same exact students had a difficult time of it.
We did a study at the AHPCRC attempting to measure the "ease of programming"
of MPI versus UPC/CAF. Having observed how it was done, the mix of experience
in the group looked at, and noting the complexity of measuring "ease of programming"
I would say the conclusions drawn were of nearly no value.
Explicitness (MPI) tends to force one to think for carefully of the potential pits falls
and complexities of the coding problem (in some cases delivering better code), while
slowing you down in the short-run. Implicitness (UPC,CAF, OpenMP) tends to speed
the initial development of the code, while allowing more novice programmers to make
both parallel programming and performance errors. This tendency is reflected in the
design ideas behind UPC (more implicit shared memory references) and CAF (more
explicit shared memory references). While both are small foot print, I tend to like the
CAF model better which reminds the programmer of every remote reference with a
square bracket at the end of its co-array expressions (Raffeinert es herr CAF, aber
boshaft es herr nicht ... ;-) ...)
I might add a point beyond ease-of-use related to granularity ... coding some algorithms
that have a natural fine-grained-ness can be prevented entirely by the cumbersomeness
explicit message passing models. The algorithmic flexibiltiy provided by small foot-print shared
memory and PGAS models can be a liberating experience for the programmer, just like a very good
symbolism can be in mathematics. Of course, across the spectrum of commodity resources
OpenMP does not scale, and UPC and CAF do not yet equal the performance of well-
written MPI code. Although it would seem that much MPI code is not that "well-written".
As to how parallel programming will evolve in this context I think that my signature quote
below is relevant.
"Making predictions is hard, especially about the future."
Thrashing River Consulting--
5605 Alameda St.
Shoreview, MN 55126
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