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Title: In Situ Methods, Infrastructures, and Applications on High Performance Computing Platforms, a State-of-the-art (STAR) Report

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.
Authors:
; ; ; ; ; ; ; ; ; ;
Publication Date:
Grant/Contract Number:
AC02-05CH11231
Type:
Accepted Manuscript
Journal Name:
Computer Graphics Forum
Additional Journal Information:
Journal Volume: 35; Journal Issue: 3; Conference: Eurovis 2016, Groningen, The Netherlands, June 2016; Related Information: LBNL-1005709; Journal ID: ISSN 0167-7055
Publisher:
Wiley
Research Org:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)
Country of Publication:
United States
Language:
English
OSTI Identifier:
1439995

Bethel, EW, Bauer, A, Abbasi, H, Ahrens, J, Childs, H, Geveci, B, Klasky, S, Moreland, K, O'Leary, P, Vishwanath, V, and Whitlock, B. In Situ Methods, Infrastructures, and Applications on High Performance Computing Platforms, a State-of-the-art (STAR) Report. United States: N. p., Web. doi:10.1111/cgf.12930.
Bethel, EW, Bauer, A, Abbasi, H, Ahrens, J, Childs, H, Geveci, B, Klasky, S, Moreland, K, O'Leary, P, Vishwanath, V, & Whitlock, B. In Situ Methods, Infrastructures, and Applications on High Performance Computing Platforms, a State-of-the-art (STAR) Report. United States. doi:10.1111/cgf.12930.
Bethel, EW, Bauer, A, Abbasi, H, Ahrens, J, Childs, H, Geveci, B, Klasky, S, Moreland, K, O'Leary, P, Vishwanath, V, and Whitlock, B. 2016. "In Situ Methods, Infrastructures, and Applications on High Performance Computing Platforms, a State-of-the-art (STAR) Report". United States. doi:10.1111/cgf.12930. https://www.osti.gov/servlets/purl/1439995.
@article{osti_1439995,
title = {In Situ Methods, Infrastructures, and Applications on High Performance Computing Platforms, a State-of-the-art (STAR) Report},
author = {Bethel, EW and Bauer, A and Abbasi, H and Ahrens, J and Childs, H and Geveci, B and Klasky, S and Moreland, K and O'Leary, P and Vishwanath, V and Whitlock, B},
abstractNote = {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.},
doi = {10.1111/cgf.12930},
journal = {Computer Graphics Forum},
number = 3,
volume = 35,
place = {United States},
year = {2016},
month = {6}
}