MPMD Framework for Offloading Load Balance Computation

Olga Pearce, Todd Gamblin, Bronis R.De Supinski, Martin Schulz, Nancy M. Amato

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

4 Scopus citations

Abstract

In many parallel scientific simulations, work is assigned to processors by decomposing a spatial domain consisting of mesh cells, particles, or other elements. When work per element changes, simulations can use dynamic load balance algorithms to distribute work to processors evenly. Typical SPMD simulations wait while a load balance algorithm runs on all processors, but this algorithm can itself become a bottleneck. We propose a novel approach based on two key observations: (1) application state typically changes slowly in SPMD physics simulations, so work assignments computed in the past still produce good load balance in the future, (2) we can decouple the load balance algorithm so that it runs concurrently with the application and more efficiently on a smaller number of processors. We then apply the work assignment "late", once it has been computed. We call this approach lazy load balancing. In this paper, we show that the rate of change in work distribution is slow for a Barnes-Hut benchmark and for ParaDiS, a dislocation dynamics simulation. We implement an MPMD framework to exploit this property to save resources by running a load balancing algorithm at higher parallel efficiency on a smaller number of processors. Using our framework, we explore the trade-offs of lazy load balancing and demonstrate performance improvements of up to 46%.

Original languageEnglish
Title of host publicationProceedings - 2016 IEEE 30th International Parallel and Distributed Processing Symposium, IPDPS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages943-952
Number of pages10
ISBN (Electronic)9781509021406
DOIs
StatePublished - 18 Jul 2016
Externally publishedYes
Event30th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2016 - Chicago, United States
Duration: 23 May 201627 May 2016

Publication series

NameProceedings - 2016 IEEE 30th International Parallel and Distributed Processing Symposium, IPDPS 2016

Conference

Conference30th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2016
Country/TerritoryUnited States
CityChicago
Period23/05/1627/05/16

Keywords

  • Graph partitioning
  • Load balancing
  • Parallel simulations

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