Computational science has become a vital tool in the 21st century, central to progress at the frontiers of nearly every scientific and engineering discipline, including many areas with significant societal impact. A persistent need for more computing power has provided an impetus for the high-performance computing (HPC) community to embark upon the path to exascale computing. The challenges associated with achieving efficient, highly effective exascale computing are extraordinary. Past growth in HPC has been driven by performance and has relied on a combination of faster clock speeds and increasingly larger systems. Achieving exascale performance under reliability and power constraints and in the presence of levels of parallelism increased by orders of magnitude will change the path of system and application development, A recent DARPA study showed that even if it were technically feasible, exascale systems built following the current trajectory would require an energy budget in the hundredsof-megawatts-per-hour range and reliability estimates that would render them impractical. 1 Thus, the clock speed benefits of Moore’s law have ended, and the emphasis must now unavoidably yield to the goal of achieving performance under stringent power and reliability constraints. The clock speed benefits of Moore’s law have ended, and researchers must codesign future exascale HPC systems and applications concurrently in an integrated manner to achieve higher performance under stringent power and reliability constraints.
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