Inshimtu – A Lightweight In Situ Visualization “Shim”

by J. Kress, G. Holst, H. P. Dasari, S. Afzal, I. Hoteit, T. Theußl
Conference Paper Year:2023 DOI: 10.1007/978-3-031-40843-4_19

Bibliography

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Volume 13999 LNCS, Pages 257 - 268, 2023, Code 294749

Abstract

In situ visualization and analysis is a valuable yet under utilized commodity for the simulation community. There is hesitance or even resistance to adopting new methodologies due to the uncertainties that in situ holds for new users. There is a perceived implementation cost, maintenance cost, risk to simulation fault tolerance, potential lack of scalability, a new resource cost for running in situ processes, and more. The list of reasons why in situ is overlooked is long. We are attempting to break down this barrier by introducing Inshimtu. Inshimtu is an in situ “shim” library that enables users to try in situ before they buy into a full implementation. It does this by working with existing simulation output files, requiring no changes to simulation code. The core visualization component of Inshimtu is ParaView Catalyst, allowing it to take advantage of both interactive and non-interactive visualization pipelines that scale. We envision Inshimtu as stepping stone to show users the value of in situ and motivate them to move to one of the many existing fully-featured in situ libraries available in the community. We demonstrate the functionality of Inshimtu with a scientific workflow on the Shaheen II supercomputer. Inshimtu is available for download at: https://github.com/kaust-vislab/Inshimtu-basic.

Keywords

Cost maintenance Implementation cost In-situ process Maintenance cost Resource costs Running-in Situ analysis Situ visualization Uncertainty Visualization and analysis
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