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OpenSHMEM Active Message Extension for Task-Based Programming

  • Wenbin Lu
  • , Tony Curtis
  • , Barbara Chapman
  • Stony Brook University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

As a lightweight library-based Partitioned Global Address Space (PGAS) programming model, OpenSHMEM provides efficient one-sided and collective communications and is receiving more attention in recent years. However, task-based programming models are getting bigger traction in scientific computing communities. Application developers are attracted by their ability to achieve better load balance in the face of ever-growing application complexity, and the increasing on-node parallelism in modern high-performance computing machines. Although communication contexts provide threads with first-class access to the network in the OpenSHMEM+X model, OpenSHMEM still has very limited ability to perform advanced operations found in other task-based models. For example, compared to the remote procedure call (RPC) mechanism in the UPC++ programming model, more work is required if the signal/wait routines are used to achieve similar remote task launching operations. In this paper, we introduce a lightweight active message (AM) extension to OpenSHMEM that is designed to perform short, non-blocking remote function invocations. This extension aims to bring some benefits of task-based programming to OpenSHMEM without making it a full-blown heavyweight tasking system with a sophisticated scheduler. We study the performance of this active message extension by running micro-benchmarks, and by evaluating its computation efficiency at different task granularities using the TaskBench framework.

Original languageEnglish
Title of host publicationOpenSHMEM and Related Technologies. OpenSHMEM in the Era of Exascale and Smart Networks - 8th Workshop on OpenSHMEM and Related Technologies, OpenSHMEM 2021, Revised Selected Papers
EditorsStephen Poole, Oscar Hernandez, Matthew Baker, Tony Curtis
PublisherSpringer Science and Business Media Deutschland GmbH
Pages129-143
Number of pages15
ISBN (Print)9783031048876
DOIs
StatePublished - 2022
Event8th Workshop on OpenSHMEM and Related Technologies, OpenSHMEM 2021 - Virtual, Online
Duration: Sep 14 2021Sep 16 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13159 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th Workshop on OpenSHMEM and Related Technologies, OpenSHMEM 2021
CityVirtual, Online
Period09/14/2109/16/21

Keywords

  • Active message
  • OpenSHMEM
  • PGAS
  • Tasking

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