量化实现百亿亿次计算的能源效率挑战

J. Mair, Zhiyi Huang, D. Eyers, Yawen Chen
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引用次数: 25

摘要

在超级计算机的设计中,功率和性能是两个潜在的对立目标,性能的提高通常是以功耗的增加为代价的,反之亦然。同时最大化这两个目标的任务正在成为未来百亿亿次超级计算机发展中日益突出的挑战。为了了解挑战的规模,我们分析了Top500和Green500超级计算机列表的功率和性能趋势。然后,我们提出了PαPW度量,我们用它来评估功率效率的可扩展性,预测一个百亿亿级系统的发展。从这一分析中,我们发现,当考虑到功率和性能时,实现百亿亿级系统的预计日期远远超出了目前的2020年目标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quantifying the Energy Efficiency Challenges of Achieving Exascale Computing
Power and performance are two potentially opposing objectives in the design of a supercomputer, where increases in performance often come at the cost of increased power consumption and vice versa. The task of simultaneously maximising both objectives is becoming an increasingly prominent challenge in the development of future exascale supercomputers. To gain some perspective on the scale of the challenge, we analyse the power and performance trends for the Top500 and Green500 supercomputer lists. We then present the PαPW metric, which we use to evaluate the scalability of power efficiency, projecting the development of an exascale system. From this analysis, we found that when both power and performance are considered, the projected date of achieving an exascale system falls far beyond the current target of 2020.
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