<i>In Situ</i>Methods, Infrastructures, and Applications on High Performance Computing Platforms

Andrew Bauer(Kitware (United States)), Hasan Abbasi(Oak Ridge National Laboratory), James Ahrens(Los Alamos National Laboratory), Hank Childs(University of Oregon), Berk Geveci(Kitware (United States)), Scott Klasky(Oak Ridge National Laboratory), Kenneth Moreland(Sandia National Laboratories), Patrick O’Leary(Kitware (United States)), Venkatram Vishwanath(Argonne National Laboratory), Brad Whitlock(Intelligent Light (United States)), E. Wes Bethel(Lawrence Berkeley National Laboratory)
Computer Graphics Forum
June 1, 2016
Cited by 148Open Access
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Abstract

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.


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