Still unresolved is how well biotech-industry software can run on both smaller computers and teraflop behemoths, and whether centralized supercomputers can yield useful results for an industry that wants to analyze unrelated data on patients' genetic makeup, hometown climate, and lifestyle choices--anything that could describe why different groups of people respond differently to the same drugs. "Just programming these monsters is problematic enough," Peterson says. "Then we have to deal with data access and the grid. All the data we need is not going to sit around that big computer. We're still trying to find the killer app."
IBM is trying to simplify the search. Blue Gene was conceived of as a computer to simulate protein-folding, a mysterious bodily process that could shed light on disease formation if it's well understood. That work is still under way--a small version of Blue Gene/L can run one protein simulation 12 times faster than IBM's popular SP supercomputers, Pulleyblank says. This summer, the company plans to start testing a broader palette of software with business appeal: Seismic imaging apps that help oil companies find petroleum reserves, computational chemistry software for biotech, and business-intelligence software for analyzing sales data. IBM this summer also plans to bring a Blue Gene/L machine online at its computing center in Poughkeepsie, N.Y., making time available to select customers over the Internet. Yet another pilot involves testing derivatives-pricing software with an unnamed bank. "IBM's a big company. They don't make a living on things you just sell to universities," says Phil Andrews, director of high-end computing at the San Diego Supercomputer Center.
More companies are incorporating high-performance workloads into their everyday computing chores. Businesses have been able to deploy mini-supers on the cheap by linking hundreds or thousands of PCs over standard Ethernet networks. But those clusters, and even more sophisticated "massively parallel processing" supercomputers such as IBM's SP, are tricky to program and spend lots of time waiting for data to show up from memory, slowing performance. And some users question whether Linux clusters' performance gains can last as systems grow bigger.
Derek Budworth, director of enterprise storage and servers at Boeing Co., says the PC clusters it uses for military contracts compute more cheaply than the 112-processor X1 supercomputer from Cray that it installed this year, largely to design Boeing's 7E7 Dreamliner, a super-efficient midsize jet scheduled to fly in '08. But getting answers takes longer with the lower-cost approach. "You have a trade-off between how soon you need your results and how much you want to pay," he says.
With Blue Gene, IBM says it can deliver world-beating performance at cluster prices--about $1 per million calculations per second, versus several dollars a megaflop for a specialized supercomputer like Cray's new X1. Pulleyblank says Blue Gene is meant to tackle the big issues holding back performance and affordability of supercomputers: slow data-shuttling, power-hungry and hot-running designs, and the tendency to consume lots of expensive real estate.
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