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The Landscape of Exascale Research: A Data-Driven Literature Analysis

机译:Exascale Research景观:数据驱动文献分析

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摘要

The next generation of supercomputers will break the exascale barrier. Soon we will have systems capable of at least one quintillion (billion billion) floating-point operations per second (10(18) FLOPS). Tremendous amounts of work have been invested into identifying and overcoming the challenges of the exascale era. In this work, we present an overview of these efforts and provide insight into the important trends, developments, and exciting research opportunities in exascale computing. We use a three-stage approach in which we (1) discuss various exascale landmark studies, (2) use data-driven techniques to analyze the large collection of related literature, and (3) discuss eight research areas in depth based on influential articles. Overall, we observe that great advancements have been made in tackling the two primary exascale challenges: energy efficiency and fault tolerance. However, as we look forward, we still foresee two major concerns: the lack of suitable programming tools and the growing gap between processor performance and data bandwidth (i.e., memory, storage, networks). Although we will certainly reach exascale soon, without additional research, these issues could potentially limit the applicability of exascale computing.
机译:下一代超级计算机将打破Exascale障碍。很快我们将拥有能够每秒至少一个千万亿张浮点的系统(10(18)个拖伏)。已经投入了巨大的工作,以识别和克服ExaScale时代的挑战。在这项工作中,我们概述了这些努力,并提供了进入Exascale Computing中的重要趋势,发展和令人兴奋的研究机会的洞察。我们使用三阶段方法,其中我们(1)讨论各种Exascale地标研究,(2)使用数据驱动技术来分析大量相关文献,(3)基于有影响力的文章讨论八个研究领域。总体而言,我们观察到,在解决两个主要Exascale挑战方面取得了巨大的进步:能效和容错。但是,正如我们期待的那样,我们仍然预见了两个主要问题:缺乏合适的编程工具和处理器性能和数据带宽之间的缺陷(即,内存,存储,网络)。虽然我们肯定会很快到达ExaScale,但没有额外的研究,这些问题可能会限制Exascale计算的适用性。

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