SYSTEMS

A team led by NVIDIA has been awarded a research grant of $25 million by the Defense Advanced Research Projects Agency (DARPA), the U.S. Defense Department's research and development arm, to address what the agency calls a "crisis in computing."

The four-year research contract, awarded under DARPA's Ubiquitous High Performance Computing (UHPC ) program, covers work to develop GPU technologies required to build the new class of exascale supercomputers which will be 1,000-times more powerful than today's fastest supercomputers.

The team -- which also includes Cray, Oak Ridge National Laboratory and six top U.S. universities -- is being funded by DARPA to address the challenge that conventional computing architectures are reaching the practical limits of energy usage and will not meet the challenges of exascale computing. The research team plans to develop new software and hardware technology to dramatically increase computing performance, programmability and reliability.

"This recognizes NVIDIA's substantial investments in the field of parallel processing and highlights GPU Computing's position as one of the most promising paths to exascale computing," said Bill Dally, NVIDIA's chief scientist and senior vice president of research, and the team's principal investigator. "We look forward to collaborating to develop programmable, scalable systems that operate in tight power budgets and deliver increases in performances that are many orders of magnitude above today's systems."

"The DARPA UHPC program is attacking technical issues that are key to the future of high performance computing, from the embedded terascale to the exascale," said Steve Scott, Cray's senior vice president and CTO, and the Cray principal investigator on the team. "We are excited to be working with this team, and we believe the directions we are pursuing will lead to radical improvements to the state-of-the-art in the coming decade."

In addition to the NVIDIA-led team, DARPA awarded contracts to three other teams to study UHPC systems. Prototype systems are expected to be completed by 2018.