Large scale problem solving using automatic code generation and distributed visualization

Andrei Hutanu, Erik Schnetter, Werner Benger, Eloisa Bentivegna, Alex Clary, Peter Diener, Jinghua Ge, Robert Kooima, Oleg Korobkin, Kexi Liu, Frank Löffler, Ravi Paruchuri, Jian Tao, Cornelius Toole, Adam Yates, Gabrielle Allen

Research output: Contribution to journalArticlepeer-review

Abstract

Scientific computation faces multiple scalability challenges in trying to take advantage of the latest generation compute, network and graphics hardware. We present a comprehensive approach to solving four important scalability challenges: programming productivity, scalability to large numbers of processors, I/O bandwidth, and interactive visualization of large data. We describe a scenario where our integrated system is applied in the field of numerical relativity. A solver for the governing Einstein equations is generated and executed on a large computational cluster; the simulation output is distributed onto a distributed data server, and finally visualized using distributed visualization methods and high-speed networks. A demonstration of this system was awarded first place in the IEEE SCALE 2009 Challenge.

Original languageEnglish (US)
Pages (from-to)205-220
Number of pages16
JournalScalable Computing
Volume11
Issue number2
StatePublished - Jan 1 2010
Externally publishedYes

Keywords

  • Computer algebra systems
  • Data intensive applications
  • Distributed systems
  • High performance computing
  • High speed networks
  • Problem solving environment
  • Scientific visualization

ASJC Scopus subject areas

  • Computer Science(all)

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