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<item>
  <id>05978096</id>
  <dt>a</dt>
  <an>05978096</an>
  <augroup>
    <au>Albing, Carl</au>
    <au>Troullier, Norm</au>
    <au>Whalen, Stephen</au>
    <au>Olson, Ryan</au>
    <au>Glenski, Joe</au>
    <au>Pritchard, Howard</au>
    <au>Mills, Hugo</au>
  </augroup>
  <ti>Scalable node allocation for improved performance in regular and anisotropic 3D torus supercomputers.</ti>
  <so>Cotronis, Yiannis (ed.) et al., Recent advances in the message passing interface. 18th European MPI users' group meeting, EuroMPI 2011, Santorini, Greece, September 18--21, 2011. Proceedings. Berlin: Springer (ISBN 978-3-642-24448-3/pbk). Lecture Notes in Computer Science 6960, 61-70 (2011).</so>
  <py>2011</py>
  <pu>Berlin: Springer</pu>
  <lagroup>
    <la>EN</la>
  </lagroup>
  <ccgroup>
  </ccgroup>
  <utgroup>
    <ut>resource management</ut>
    <ut>application placement</ut>
    <ut>scheduling</ut>
    <ut>topology placement</ut>
    <ut>software performance</ut>
  </utgroup>
  <cigroup>
  </cigroup>
  <ligroup>
    <li>doi:10.1007/978-3-642-24449-0_9</li>
  </ligroup>
  <abgroup>
    <ab>Summary: MPI application performance can vary based on the scheduler's placing of ranks, whether between nodes or on cores in the same multi-core chip. MPI applications, by default, are at the mercy of the application placement software decision that assigns nodes to a job. We describe herein the general approach of node ordering for allocation in a 3D torus, how it improved MPI application performance, even in the face of an anisotropic interconnect. We demonstrate, quantitatively, that our topologically-based ordering results in improved performance for several MPI applications running on a Top10 supercomputer.</ab>
    <rv></rv>
  </abgroup>
</item>