Lessons Learned from Building In Situ Coupling FrameworksReport as inadecuate

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1 ANL - Argonne National Laboratory Lemont 2 KerData - Scalable Storage for Clouds and Beyond Inria Rennes – Bretagne Atlantique , IRISA-D1 - SYSTÈMES LARGE ÉCHELLE 3 MOAIS - PrograMming and scheduling design fOr Applications in Interactive Simulation Inria Grenoble - Rhône-Alpes, LIG - Laboratoire d-Informatique de Grenoble 4 Université Grenoble Alpes Saint Martin d-Hères

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.

Keywords : Swift FlowVR Decaf Damaris Coupling Simulation In Situ Visualization Exascale

Author: Matthieu Dorier - Matthieu Dreher - Tom Peterka - Gabriel Antoniu - Bruno Raffin - Justin M. Wozniak -

Source: https://hal.archives-ouvertes.fr/


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