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HPDC '20: Proceedings of the 29th International Symposium on High-Performance Parallel and Distributed Computing
ACM2020 Proceeding
Publisher:
  • Association for Computing Machinery
  • New York
  • NY
  • United States
Conference:
HPDC '20: The 29th International Symposium on High-Performance Parallel and Distributed Computing Stockholm Sweden June 23 - 26, 2020
ISBN:
978-1-4503-7052-3
Published:
23 June 2020
Sponsors:
University of Arizona, SIGHPC, SIGARCH

Bibliometrics
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Abstract

We sincerely hope you and your families are safe and healthy.

Welcome to the International Symposium on High-Performance Parallel and Distributed Computing (ACM HPDC 2020), the premier conference at the intersection of high performance, parallel and distributed computing, now in its 29th year. ACM HPDC continues to focus on high-performance parallel and distributed computing topics including platforms spanning clouds, clusters, grids, big data, massively multicore, and extreme-scale computing systems. One of the unique features of HPDC is that it welcomes a blend of ideas ranging from translational and applied research in the form of experience papers on operational deployments and applications, to papers focused on more fundamental research in parallel and distributed techniques and systems. The conference has always appreciated the heroic efforts required to deploy real systems and applications and the insights gained from live measurement and experimentation. The HPDC 2020 program is no exception, with topics ranging from hybrid systems, scalable graph processing, GPU applications, and cloud systems, to name a few. As in previous years, the conference will include exciting workshops focused on cutting edge topics.

Given the rapidly evolving situation surrounding the COVID-19 pandemic, the HPDC 2020 conference leadership has decided to cancel the physical in-person meeting and move the conference online this year. The decision to cancel the in-person meeting does not impact the publication of the HPDC 2020 proceedings.

Contributors
  • The University of Utah
  • KTH Royal Institute of Technology
  • University of Massachusetts Amherst
  • Lawrence Livermore National Laboratory

Recommendations

Acceptance Rates

Overall Acceptance Rate 166 of 966 submissions, 17%
YearSubmittedAcceptedRate
HPDC '191062221%
HPDC '181112220%
HPDC '171001919%
HPDC '161292016%
HPDC '151161916%
HPDC '141302116%
HPDC '131312015%
HPDC '121432316%
Overall96616617%