Saturday, May 9, 2009

High Performance, Parallel, & Grid Computing

On Wednesday night (May 6th), I attended an alumni event held by the UMass Boston CS Department in the beautiful five year old Campus Center.  It was great to see my professors and former classmates, along with talking with current students about their software engineering projects.  Toward the end of the event, there was a talk given by an alumnus named Richard Anderson, the CTO of Symmetric Computing, a company that makes hardware and OS-level software for High Performance Computing (HPC).  Their slogan is something along the lines of “Supercomputing for the Masses”.  The speaker gave a fairly typical overview of the history of CPU performance, including references to Moore’s Law, hitting the gigahertz wall, and the emergence of multi-core chips, followed by a discussion of parallel programming.  He mentioned several times that the company would be making one of their 48 core/350GB systems available to the university for academic use.  It was a decent talk, if not extremely exciting.  It made me think of concurrent programming, grid/cloud computing, and the cool compute appliances made by Azul Systems.  Based on questions asked by myself and others, I was disappointed to discover that although the technical gap between HPC and the rest of the computing world is narrowing, most of the HPC world seems unaware of this.  A lot of work has gone into making clusters of commodity hardware work together and coding for these architectures easier (think Google, Map/Reduce, etc.).  It would be nice if people in HPC and distributed computing could do a better job of exchanging ideas.  Even if typical clusters have to deal with latency issues and the inability to directly access large amounts of memory, that doesn’t explain why someone should code an HPC app in Fortran or C on a Symmetric box instead of in Java on a 432 core/384GB Azul box.
I realize that this is a bit of a rant.  If any readers can provide counter-arguments or counter-examples, I’d be happy (and reassured) to read and know about them.
Update: I forgot to mention that if you’re doing academic research or teaching a class in clustering/distributed computing, you should check out the fairly new Amazon Web Services in Education program.  They provide free credits to educators, researchers, and students.  Pretty cool!


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