HPCwire: HPCS: The Big Picture

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April 07, 2006

HPCS: The Big Picture

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DARPA's High Productivity Computer Systems (HPCS) program is an ambitious attempt to propel supercomputing to the next level. In this special issue of HPCwire, each HPCS-funded vendor (Cray, IBM and Sun Microsystems) has provided us with a description of their proposed design -- the three feature articles that follow this one discuss their individual approaches.

But before you delve into the details, you may want to read one man's perspective of what DARPA's HPCS program means to the high performance computing community. HPCwire recently spoke with Douglass Post, chief scientist at the DoD High Performance Computing Modernization Program, to give us his impressions of the program. The text that follows is an excerpt from a longer interview that will be featured in an upcoming issue.

HPCwire: Can you help us understand the big picture of the DARPA HPCS program?

Post: The DARPA High Productivity Computing Systems program is a program funded by the DoD Defense Advanced Research Project Agency. It has the goal of supporting industry to develop the ability to manufacture and deliver a petaflop-class computer that is substantially easier to program and use than the computers the industry is evolving toward today. The program addresses high-performance computing as an integrated activity involving high-performance computers, programmer and code developers, and production users and seeks improvements in the whole system. A large part of the growth in computer performance is being achieved by increased computer architecture complexity. This makes it very challenging to develop codes to take advantage of the increased computer power.

A goal of the HPCS program is to reduce the "time to solution" both for production runs and for code development. The HPCS program calls for the development of computer hardware that emphasizes increased computer power for both floating point and integer arithmetic, large memories, and high bandwidth (for low memory latency) and other features that improve the ability of computational scientists and engineers to develop and run codes that can fully exploit the power of supercomputing. From what I have seen, the computer vendors (IBM, Cray and Sun in Phase II) have really looked hard at what they can do to make a computer that is orders of magnitude more productive than a traditional Linux cluster. They have developed some exciting new hardware and software technologies, and I judge that an HPCS-class machine will enable computational science and engineering to address whole new classes of problems.

The emphasis on productivity is a key part of the program. The program also has a software emphasis. It's very much not the "build it and they will come" approach. There is an effort to develop benchmarks that measure the performance of computers for the applications that are important to computational scientists and engineers. There is an emphasis on developing ways to quantify productivity for code development and production. Unless we can quantify productivity, it will never be on the same footing as FLOPS/dollar in computer procurement evaluations, and we will continue to get computers that can do a great job of running Linpack, but don't do nearly as well with most real applications, and are very challenging to develop codes for and run on.

The productivity team has been doing detailed case studies of representative scientific and engineering code projects to identify the characteristics of application codes, the workflows for code development and production, "bottlenecks" and obstacles for code development and production, and "lessons learned" so that decisions by the productivity team and the vendors are based on real data rather than anecdotal data. The potential vendors are developing new computer languages and tools that improve productivity by allowing programmers to express parallelism at higher levels of abstraction. The "catch 22" issue with new languages is that no one will use the new language until it is mature, and it will never become mature unless it is used. This has led an effort to consolidate the language efforts of the vendors to produce a single new language that the community can adopt.

This summer, the program will enter Phase III when DARPA selects one or two of the Phase II vendors (Cray, IBM and Sun) for funding to be able to accept orders for a multi-petaflop computer in 2010 from prospective customers.

In the interest of full disclosure, I believe so strongly in the goals of the program that I joined the Productivity Team several years ago.

HPCwire: Do you think we need to move beyond the legacy HPC programming languages -- C, Fortran, MPI -- to be able to take advantage of petascale-level hardware?

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