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Federated computing for the masses - Aggregating resources to tackle large-scale engineering problems

  • Javier Diaz-Montes
  • , Yu Xie
  • , Ivan Rodero
  • , Jaroslaw Zola
  • , Baskar Ganapathysubramanian
  • , Manish Parashar
  • Rutgers - The State University of New Jersey, New Brunswick
  • Iowa State University

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

The complexity of many problems in science and engineering requires computational capacity exceeding what the average user can expect from a single computational center. While many of these problems can be viewed as a set of independent tasks, their collective complexity easily requires millions of core-hours on any high-power computing (HPC) resource, and throughput that can't be sustained by a single, multiuser queuing system. An exploration of the use of aggregated HPC resources to solve large-scale engineering problems shows that it's possible to build a computational federation that's easy for end users to implement, and is elastic, resilient, and scalable. Here, the authors argue that the fusion of federated computing and real-life engineering problems can be brought to the average user if relevant middleware is provided. They report on the use of federation of 10 distributed heterogeneous HPC resources to perform a large-scale interrogation of the parameter space in the microscale fluid flow problem.

Original languageEnglish
Article number6695747
Pages (from-to)62-72
Number of pages11
JournalComputing in Science and Engineering
Volume16
Issue number4
DOIs
StatePublished - 2014

Keywords

  • Cloud computing
  • Federated computing
  • Fluid flow
  • Large-scale engineering problems
  • Scientific computing
  • Software-defined infrastructure

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