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US government hands $19m to Intel for exascale computing research

Should pay the power bills for a few months
Mon Jul 16 2012, 14:21
Intel 4004 Microprocessor

CHIPMAKER Intel has won a $19m research contract from the US government to research exascale computing.

Intel Federal, the arm of the chipmaker that deals with US government organisations, won a $19m research contract from the US Department of Energy to look into exascale computing techniques. The firm said that two sub-contracts will be shared between it and Lawrence Livermore National Laboratory.

Intel said its memory research will look at next-generation memory architectures to provide energy efficient clusters for high performance computing workloads. The firm said that it will be working within the US Department of Energy's Fastforward program, which is trying to develop next generation high performance computing technologies.

Intel has been working to create an exascale computing cluster for a few years and the firm's Xeon Phi co-processor is expected to play a big part in that effort. David Patterson, president of Intel Federal said, "High performance computing is a transformative technology that will allow current and future generations of scientists and engineers to develop breakthrough advancements to address our most pressing societal issues."

William Harrod, division director of research in the Department of Energy's Office of Science Advanced Scientific Computing Research organisation said, "The primary objective of the Department's Fastforward effort is to begin the long term R&D necessary to impact systems at the end of the decade. The development of entirely new high performance, energy-efficient processor and memory technologies are essential for developing Exascale systems and Intel is initiating highly innovative designs for these components."

The US Department of Energy's Fastforward program might simply refer to "next generation high performance computing technologies" but for Intel and other chip vendors it is all about achieving exascale computing, as doing that will mean hitting key performance and energy efficiency targets. µ


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