Power, Programmability, and Granularity: The Challenges of ExaScale Computing

Abstract

Reaching an ExaScale computer by the end of the decade, and enabling the continued performance scaling of smaller systems requires signifcant research breakthroughs in three key areas: power effciency, programmability, and execution granularity. To build an ExaScale machine in a power budget of 20 MW requires a 200-fold improvement in energy per instruction: from 2 nJ to 10 pJ. 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 fne granularity — down to the level of a few instructions. This talk discusses these challenges and current approaches to address them.