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Lessons Learned from Building In Situ Coupling Frameworks

Abstract : Over the past few years, the increasing amounts of data produced by large-scale simulations have motivated a shift from traditional offline data analysis to in situ analysis and visualization. In situ processing began as the coupling of a parallel simulation with an analysis or visualization library, motivated primarily by avoiding the high cost of accessing storage. Going beyond this simple pairwise tight coupling, complex analysis workflows today are graphs with one or more data sources and several interconnected analysis components. In this paper, we review four tools that we have developed to address the challenges of coupling simulations with visualization packages or analysis workflows: Damaris, Decaf, FlowVR and Swift. This self-critical inquiry aims to shed light not only on their potential, but most importantly on the forthcoming software challenges that these and other in situ analysis and visualization frameworks will face in order to move toward exascale.
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Submitted on : Tuesday, November 10, 2015 - 1:16:30 PM
Last modification on : Wednesday, July 6, 2022 - 4:24:10 AM
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Matthieu Dorier, Matthieu Dreher, Tom Peterka, Gabriel Antoniu, Bruno Raffin, et al.. Lessons Learned from Building In Situ Coupling Frameworks. ISAV 2015 - First Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization (held in conjunction with SC15), Nov 2015, Austin, United States. ⟨10.1145/2828612.2828622⟩. ⟨hal-01224846⟩



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