David Patterson had a great idea. Two years ago, the eminent computer scientist, a professor at the University of California, Berkeley, was looking at recent advances in statistical machine learning, an area within artificial intelligence involving how computers can learn automatically. It occurred to him that the technology had enormous potential to make distributed computer systems, military as well as commercial, more stable and robust. So he contacted the logical source to fund such an idea: the Defense Advanced Research Projects Agency, or DARPA, the U.S. Department of Defense organization known for backing long-range, blue-sky research.
To his surprise, he was refused. "They didn't even respond for many months, and then it was just a perfunctory rejection," recalls Patterson, an IEEE Fellow and president of the Association for Computing Machinery, in New York City. He next tried the National Science Foundation, in Arlington, Va., but was again turned down. Talking to his Berkeley colleagues, who'd also had grant proposals declined, Patterson says, "We came to the conclusion that the style of high-risk, high-impact research we've been doing, involving 3 to 6 faculty and maybe 20 to 30 graduate students, was going to be a problem."
So Patterson went looking elsewhere for money, and in December, he announced the creation of the Reliable, Adaptive, and Distributed Systems Laboratory--or RAD Lab--jointly funded by Google, Microsoft, and Sun Microsystems, each of which will give the lab US $500 000 annually for five years [see photo, " "]. The IT industry has sponsored many university-based projects, but this may be the first to be formed out of frustration with the current funding climate in Washington. "In this era of increasing competitive pressures, people tend to get conservative, and descriptions like 'ambitious proposal' tend to be a negative," Patterson notes. "We had to find another model."
Much of the frustration among computer scientists has been aimed at DARPA. Not only has the level of support plummeted, critics say, but the money is going toward near-term projects with a strictly military focus. By the agency's own accounting, it awarded universities $207 million in 2002 for computer science research, but only $123 million in 2004. (These figures don't include grants under which a university served as a subcontractor or did classified work; factoring in those sources, university funding in computer science dropped from $215 million to $161 million.) Meanwhile, DARPA's overall budget has been steadily rising. In fiscal year 2003, the agency received $2.7 billion; last year it got just under $3 billion, and the 2006 request is $3.1 billion.
The other main government backer of university computer science research in the United States is the National Science Foundation. Funding there actually doubled between 1999 and 2005, to close to $500 million, according to Peter Freeman, assistant director for NSF's Computer and Information Science and Engineering Directorate. But computer science is growing even faster, he says. While in years past, the directorate supported 30 to 35 percent of the proposals it received, by 2004 the funding rate had been halved, to 16 percent, while in 2005 it was 21 percent.
NSF grants tend to be small--typically $150 000 or less, which is enough to support one professor over the summer, plus a couple of graduate students. That's far too little to sustain large, multiyear undertakings like Patterson's or like a project developed by computer scientists Doug Burger and Steve Keckler at the University of Texas at Austin. In 2000 the two associate professors began sketching out a new scalable architecture for high-performance microprocessors. Such devices could eventually allow a single chip to perform trillions of calculations per second and be useful in signal processors, servers, desktop computers, and embedded systems.