Implementing MPI on the BlueGene/L Supercomputer

  • George Almási
  • Charles Archer
  • José G. Castaños
  • C. Chris Erway
  • Philip Heidelberger
  • Xavier Martorell
  • José E. Moreira
  • Kurt Pinnow
  • Joe Ratterman
  • Nils Smeds
  • Burkhard Steinmacher-burow
  • William Gropp
  • Brian Toonen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3149)

Abstract

The BlueGene/L supercomputer will consist of 65,536 dual-processor compute nodes interconnected by two high-speed networks: a three-dimensional torus network and a tree topology network. Each compute node can only address its own local memory, making message passing the natural programming model for BlueGene/L. In this paper we present our implementation of MPI for BlueGene/L. In particular, we discuss how we leveraged the architectural features of BlueGene/L to arrive at an efficient implementation of MPI in this machine. We validate our approach by comparing MPI performance against the hardware limits and also the relative performance of the different modes of operation of BlueGene/L. We show that dedicating one of the processors of a node to communication functions greatly improves the bandwidth achieved by MPI operation, whereas running two MPI tasks per compute node can have a positive impact on application performance.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • George Almási
    • 1
  • Charles Archer
    • 2
  • José G. Castaños
    • 1
  • C. Chris Erway
    • 1
  • Philip Heidelberger
    • 1
  • Xavier Martorell
    • 1
  • José E. Moreira
    • 1
  • Kurt Pinnow
    • 2
  • Joe Ratterman
    • 2
  • Nils Smeds
    • 1
  • Burkhard Steinmacher-burow
    • 1
  • William Gropp
    • 3
  • Brian Toonen
    • 3
  1. 1.IBM Thomas J. Watson Research CenterYorktown HeightsUSA
  2. 2.IBM Systems GroupRochesterUSA
  3. 3.Mathematics and Computer Science DivisionArgonne National LaboratoryArgonneUSA

Personalised recommendations