Reference Exascale Architecture (Extended Version)

Authors

  • Martin Bobák Institute of Informatics, Slovak Academy of Sciences, 845 07 Bratislava, Slovakia
  • Ladislav Hluchý Institute of Informatics, Slovak Academy of Sciences, 845 07 Bratislava, Slovakia
  • Ondrej Habala Institute of Informatics, Slovak Academy of Sciences, 845 07 Bratislava, Slovakia
  • Viet Tran Institute of Informatics, Slovak Academy of Sciences, 845 07 Bratislava, Slovakia
  • Reginald Cushing Institute of Informatics, University of Amsterdam, Amsterdam, Netherlands
  • Onno Valkering Institute of Informatics, University of Amsterdam, Amsterdam, Netherlands
  • Adam Belloum Institute of Informatics, University of Amsterdam, Amsterdam, Netherlands
  • Mara Graziani University of Applied Sciences of Western Switzerland, 3960 Sierre, Switzerland
  • Henning Müller University of Applied Sciences of Western Switzerland, 3960 Sierre, Switzerland
  • Souley Madougou Netherlands eScience Center, 1098 XG Amsterdam, Netherlands
  • Jason Maassen Netherlands eScience Center, 1098 XG Amsterdam, Netherlands

DOI:

https://doi.org/10.31577/cai_2020_4_644

Keywords:

Exascale, architecture, validation

Abstract

While political commitments for building exascale systems have been made, turning these systems into platforms for a wide range of exascale applications faces several technical, organisational and skills-related challenges. The key technical challenges are related to the availability of data. While the first exascale machines are likely to be built within a single site, the input data is in many cases impossible to store within a single site. Alongside handling of extreme-large amount of data, the exascale system has to process data from different sources, support accelerated computing, handle high volume of requests per day, minimize the size of data flows, and be extensible in terms of continuously increasing data as well as an increase in parallel requests being sent. These technical challenges are addressed by the general reference exascale architecture. It is divided into three main blocks: virtualization layer, distributed virtual file system, and manager of computing resources. Its main property is modularity which is achieved by containerization at two levels: 1) application containers - containerization of scientific workflows, 2) micro-infrastructure - containerization of extreme-large data service-oriented infrastructure. The paper also presents an instantiation of the reference architecture - the architecture of the PROCESS project (PROviding Computing solutions for ExaScale ChallengeS) and discusses its relation to the reference exascale architecture. The PROCESS architecture has been used as an exascale platform within various exascale pilot applications. This paper also presents performance modelling of exascale platform with its validation.

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Published

2021-01-12

How to Cite

Bobák, M., Hluchý, L., Habala, O., Tran, V., Cushing, R., Valkering, O., … Maassen, J. (2021). Reference Exascale Architecture (Extended Version). COMPUTING AND INFORMATICS, 39(4), 644–677. https://doi.org/10.31577/cai_2020_4_644

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Special Section Articles

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