Scaling performance for N-body stream computation with a ring of FPGAS

Jens Huthmann, Abiko Shin, Artur Podobas, Kentaro Sano, Hiroyuki Takizawa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Field-Programmable Gate Arrays (FPGAs) oer a fairly non-invasive method to specialize custom architectures towards a specic application domain. Recent studies has successfully demonstrated that single-node FPGAs can be a rival to both CPUs and GPUs in performance. Unfortunately, most existing studies limit themselves to using a single FPGA devices, and their scalability requires more investigation. In this work, we practically demonstrate how to scale the important n-body problem across a comparatively large FPGA cluster. Our design – composed of up to 256 processing elements – achieves near-linear strong scaling, with performance-levels comparable to that of custom Application-Specic Integrated Circuits (ASICs). We further develop an analytical performance model, which we use to predict the performance of our solution onto future upcoming Intel Agilex systems. Today, our system reaches up to 47 Giga-Pairs/second, and using our performance model we predict that we can reach up-to 0.142 Tera-Pairs/second peak performance with next-generation FPGAs.

Original languageEnglish
Title of host publicationProceedings of the 10th International Symposium on Highly-Efficient Accelerators and Reconfigurable Technologies, HEART 2019
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450372558
DOIs
Publication statusPublished - 2019 Jun 6
Event10th International Symposium on Highly-Efficient Accelerators and Reconfigurable Technologies, HEART 2019 - Nagasaki, Japan
Duration: 2019 Jun 62019 Jun 7

Publication series

NameACM International Conference Proceeding Series

Conference

Conference10th International Symposium on Highly-Efficient Accelerators and Reconfigurable Technologies, HEART 2019
CountryJapan
CityNagasaki
Period19/6/619/6/7

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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