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Federated Computing for the Masses – Aggregating Resources to Tackle Large-scale Engineering Problems
Computing in Science & Engineering
  • Javier Diaz-Montes, Rutgers University
  • Yu Xie, Iowa State University
  • Ivan Rodero, Rutgers University
  • Jaroslaw Zola, Rutgers University
  • Baskar Ganapathysubramanian, Iowa State University
  • Manish Parashar, Rutgers University
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The complexity of many problems in science and engineering requires computational capacity exceeding what 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 core-hours on any state-of-the-art HPC resource, and throughput that cannot be sustained by a single multi-user queuing system. In this paper we explore the use of aggregated HPC resources to solve large-scale engineering problems. We show it is possible to build a computational federation that is easy to use by end-users, and is elastic, resilient and scalable. We argue that the fusion of federated computing and real-life engineering problems can be brought to average user if relevant middleware is provided. We 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.

This is a manuscript of an article published as Diaz-Montes, Javier, Yu Xie, Ivan Rodero, Jaroslaw Zola, Baskar Ganapathysubramanian, and Manish Parashar. "Federated Computing for the Masses--Aggregating Resources to Tackle Large-Scale Engineering Problems." Computing in Science & Engineering 16, no. 4 (2014): 62-72. DOI:10.1109/MCSE.2013.134. Posted with permission.

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Javier Diaz-Montes, Yu Xie, Ivan Rodero, Jaroslaw Zola, et al.. "Federated Computing for the Masses – Aggregating Resources to Tackle Large-scale Engineering Problems" Computing in Science & Engineering Vol. 16 Iss. 4 (2014) p. 62 - 72
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