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

被引:34
|
作者
Heldens, Stijn [1 ,2 ]
Hijma, Pieter [2 ,3 ]
van Werkhoven, Ben [1 ]
Maassen, Jason [1 ]
Belloum, Adam S. Z. [2 ]
Van Nieuwpoort, Rob V. [1 ]
机构
[1] Netherlands eSci Ctr, Sci Pk 140, NL-1098 XG Amsterdam, Netherlands
[2] Univ Amsterdam, Sci Pk 904, NL-1098 XH Amsterdam, Netherlands
[3] Vrije Univ Amsterdam, Boelelaan 1111, NL-1081 HV Amsterdam, Netherlands
关键词
Exascale computing; extreme-scale computing; literature review; high-performance computing; data-driven analysis; PARALLEL PROGRAMMING-MODELS; IN-SITU VISUALIZATION; NONVOLATILE MEMORY; ENERGY EFFICIENCY; CHALLENGES; SOFTWARE; RESILIENCE; SYSTEMS; CORE; OPPORTUNITIES;
D O I
10.1145/3372390
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
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.
引用
收藏
页数:43
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