In Situ Methods, Infrastructures, and Applications on High Performance Computing Platforms

A. C. Bauer, H. Abbasi, J. Ahrens, H. Childs, B. Geveci, S. Klasky, K. Moreland, P. O'Leary, V. Vishwanath, B. Whitlock, E. W. Bethel

Research output: Contribution to journalArticlepeer-review

124 Scopus citations

Abstract

The considerable interest in the high performance computing (HPC) community regarding analyzing and visualization data without first writing to disk, i. e., in situ processing, is due to several factors. First is an I/O cost savings, where data is analyzed/visualized while being generated, without first storing to a filesystem. Second is the potential for increased accuracy, where fine temporal sampling of transient analysis might expose some complex behavior missed in coarse temporal sampling. Third is the ability to use all available resources, CPU's and accelerators, in the computation of analysis products. This STAR paper brings together researchers, developers and practitioners using in situ methods in extreme-scale HPC with the goal to present existing methods, infrastructures, and a range of computational science and engineering applications using in situ analysis and visualization.

Original languageEnglish
Pages (from-to)577-597
Number of pages21
JournalComputer Graphics Forum
Volume35
Issue number3
DOIs
StatePublished - Jun 1 2016

Keywords

  • Categories and Subject Descriptors (according to ACM CCS)
  • I.3.2 [Computer Graphics]: Graphics Systems—Distributed/network graphics

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