Supercomputing turns toward productivity

To IT managers, high-stakes supercomputing may seem like the land-speed record: a freak show, amusing but hardly relevant. Oh, a car broke Mach 1? And a defense lab has a 280 TFLOPS computer? Cool. Now let’s get back to work.

However, supercomputing specialists are wrestling with problems that will affect everyday IT within the next two to five years. Essentially, improvements in processors have outstripped those in data movement. For some time now, the limiting factor in high-performance computing has been the speed with which data can be moved to and from the processors. Indeed, the cylindrical shape of the iconic Cray supercomputers is an effort to limit the distances data must flow.

Because supercomputing is the sharp end of the technology spear, these data-flow problems (still manageable in most corporate data centres) are quickly reaching critical mass in the world’s top research facilities. Breakthroughs are needed, and experts acknowledge that answers are elusive.

Backdrop: Multicore, Clusters

There are two key factors in today’s supercomputing tumult: multicore chips and the rise of “cluster” supercomputers composed of hundreds or thousands of humble Intel-style CPUs.

Multicore chips place more than one processor on a single integrated circuit. Dual-core PCs are already common, and experts believe this Moore’s Law-driven progression will continue so that by 2010, your garden-variety chip will house 64 processors.

With each of these processors running four software threads at once, 256 threads could be simultaneously executed on a single chip.

Jack Dongarra, a computer science professor at the University of Tennessee, says that more than 60 per cent of the top 500 computers are clustered rather than relying on the traditional exotic architectures most commonly associated with Seattle-based Cray Inc.

“Clusters have completely changed the scientific computing landscape,” he says, because they offer a price/performance ratio that exotic machines can’t touch.

Moreover, as clusters have become popular, users have found “a surprisingly large number of real-world applications that do not require the extreme latency and bandwidth capabilities of the exotics,” says Justin Rattner, a distinguished fellow at Intel Corp.

However, as users call for more powerful tools, Cray executives believe the supercomputing pendulum is swinging back their way — and some research scientists agree.

Indeed, they say, it’s possible that before 2015, exotic supercomputers, with their benefits of low latency and high bandwidth, will join clusters, with their price advantage, in hybrid architectures suitable for a variety of applications.

Plan Ahead

To exploit the parallelism inherent in software as fully as possible, IBM Research, among others, is trying to allow processes to run out of order and then be reassembled on the fly in a process it calls speculative multithreading. Al Gara, chief architect for IBM’s Blue Gene, calls it a potential breakthrough, but as the number of threads increases, the components that must eventually be reassembled into the final result grow exponentially.

The Defense Advanced Research Projects Agency has a program called High Productivity Computing Systems aimed at doubling the productivity of scientific computers every 18 months until at least 2010. In response, several academic researchers are working on languages and compilers for parallel and high-performance computing.

For example, Ken Kennedy, director of the Center for High Performance Software Research at Rice University, is developing a system that uses a library of components to generate high-performance compilers for specific scientific domains, such as biological computing or signal processing.

“It’s important to have big computers,” he says, “but there’s two parts to that: having a computer and being able to use it. High-end computing has been overly limited to people who are really expert in programming. We have to not only go for very high performance, but for very high productivity.”

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— Ulfelder is a full-time freelance writer located in Southboro, Mass. He can be reached at

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