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Reaching an ExaScale computer by the end of the decade, and enabling the continued performance scaling of smaller systems requires significant research breakthroughs in three key areas: power efficiency, programmability, and execution granularity. To build an ExaScale machine in a power budget of 20MW requires a 200-fold improvement in energy per instruction: from 2nJ to 10pJ. Only 4x is expected from improved technology. The remaining 50x must come from improvements in architecture and circuits. To program a machine of this scale requires more productive parallel programming environments - that make parallel programming as easy as sequential programming is today. Finally, problem size and memory size constraints prevent the continued use of weak scaling, requiring these machines to extract parallelism at very fine granularity - down to the level of a few instructions. This talk will discuss these challenges and current approaches to address them.

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