MPI on a million processors

Pavan Balaji, Darius Buntinas, David Goodell, William Gropp, Sameer Kumar, Ewing Lusk, Rajeev Thakur, Jesper Larsson Träff

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


Petascale machines with close to a million processors will soon be available. Although MPI is the dominant programming model today, some researchers and users wonder (and perhaps even doubt) whether MPI will scale to such large processor counts. In this paper, we examine this issue of how scalable is MPI. We first examine the MPI specification itself and discuss areas with scalability concerns and how they can be overcome. We then investigate issues that an MPI implementation must address to be scalable. We ran some experiments to measure MPI memory consumption at scale on up to 131,072 processes or 80% of the IBM Blue Gene/P system at Argonne National Laboratory. Based on the results, we tuned the MPI implementation to reduce its memory footprint. We also discuss issues in application algorithmic scalability to large process counts and features of MPI that enable the use of other techniques to overcome scalability limitations in applications.

Original languageEnglish (US)
Title of host publicationRecent Advances in Parallel Virtual Machine and Message Passing Interface - 16th European PVM/MPI Users' Group Meeting, Proceedings
Number of pages11
ISBN (Print)3642037690, 9783642037696
StatePublished - 2009
Event16th European Parallel Virtual Machine and Message Passing Interface Users' Group Meeting, EuroPVM/MPI - Espoo, Finland
Duration: Sep 7 2009Sep 10 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5759 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other16th European Parallel Virtual Machine and Message Passing Interface Users' Group Meeting, EuroPVM/MPI

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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