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Projecting Performance Data over Simulation Geometry Using SOSflow and ALPINE

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Programming and Performance Visualization Tools (ESPT 2017, ESPT 2018, VPA 2017, VPA 2018)

Abstract

The performance of HPC simulation codes is often tied to their simulated domains; e.g., properties of the input decks, boundaries of the underlying meshes, and parallel decomposition of the simulation space. A variety of research efforts have demonstrated the utility of projecting performance data onto the simulation geometry to enable analysis of these kinds of performance problems. However, current methods to do so are largely ad-hoc and limited in terms of extensibility and scalability. Furthermore, few methods enable this projection online, resulting in large storage and processing requirements for offline analysis. We present a general, extensible, and scalable solution for in-situ (online) visualization of performance data projected onto the underlying geometry of simulation codes. Our solution employs the scalable observation system SOSflow with the in-situ visualization framework ALPINE to automatically extract simulation geometry and stream aggregated performance metrics to respective locations within the geometry at runtime. Our system decouples the resources and mechanisms to collect, aggregate, project, and visualize the resulting data, thus mitigating overhead and enabling online analysis at large scales. Furthermore, our method requires minimal user input and modification of existing code, enabling general and widespread adoption.

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Acknowledgements

The research report was supported by a grant (DE-SC0012381) from the Department of Energy, Scientific Data Management, Analytics, and Visualization (SDMAV), for “Performance Understanding and Analysis for Exascale Data Management Workflows.”

Part of this work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 (LLNL-CONF-737874).

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Wood, C. et al. (2019). Projecting Performance Data over Simulation Geometry Using SOSflow and ALPINE. In: Bhatele, A., Boehme, D., Levine, J., Malony, A., Schulz, M. (eds) Programming and Performance Visualization Tools. ESPT ESPT VPA VPA 2017 2018 2017 2018. Lecture Notes in Computer Science(), vol 11027. Springer, Cham. https://doi.org/10.1007/978-3-030-17872-7_12

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  • DOI: https://doi.org/10.1007/978-3-030-17872-7_12

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  • Online ISBN: 978-3-030-17872-7

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