Researchers at UC-Berkeley, University of Illinois and Stanford University have been at work for a little over a year with grants from Intel, Microsoft and a handful of other backers mainly from the PC industry. All three are forming ideas about the future of chips with dozens or hundreds of cores and coding prototype parallel software to harness them.

All sides see the need to rewrite today's software stack, starting with performance-hungry applications then plugging in new languages and runtime environments and rewriting or scraping traditional operating systems. They are already beginning to develop and test early versions of their code.

Work on hardware is in a more nascent stage. Most agree changes will focus on developing new memory structures, but fundamental debates about how to architect memory for many-core processors remain unresolved.

"I think we've made significant strides," said Kunle Olukotun, director of the Pervasive Parallelism Lab at Stanford. "We had this vision and have started to fill in the pieces and it feels like the vision really in really coming to pass," he said.

The labs hope to be able to show "reasonably complete" parallel software stacks running on simulators or prototype hardware within one or two years when their grants are up for renewal. By the end of the five-year grants, they hope to have work that is solid enough to show a path for commercial use.

"We believe within four years we can show companies like Intel and Microsoft how they can make their offerings better support parallel programming," said Marc Snir, co-director of the Universal Parallel Computing Research Center (UPCRC) at the University of Illinois. "There is no silver bullet, but we hope we can make developing parallel software as easy as developing today's software," he said.

The industry expects processors with 64 cores or more will arrive by 2015, forcing the need for parallel software, said David Patterson of the Berkeley Parallel Lab. Although researchers have failed to create a useful parallel programming model in the past, he was upbeat that this time there is broad industry focus on solving the problem.