Performance Debugging and Tuning of Flash-X with Data Analysis Tools

Kevin Huck, Xingfu Wu, Anshu Dubey, Antigoni Georgiadou, J. Austin Harris, Tom Klosterman, Matthew Trappett, Klaus Weide

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

State-of-the-art multiphysics simulations running on large scale leadership computing platforms have many variables contributing to their performance and scaling behavior. We recently encountered an interesting performance anomaly in Flash-X, a multiphysics multicomponent simulation software, when characterizing its performance behavior on several large-scale HPC platforms. The anomaly was tracked down to the interaction between the use of dynamic allocation of scratch data and data locality in the cache hierarchy. In this paper we present the details of unexpected performance variability of Flash-X, its extensive analysis using the performance measurement tool TAU to collect the data and Python data analysis libraries to explore the data, and our insights from this experience. In this process, we discovered and removed or mitigated two additional performance limiting bottlenecks for performance tuning.

Original languageEnglish
Title of host publicationProceedings of ProTools 2022
Subtitle of host publicationWorkshop on Programming and Performance Visualization Tools, Held in conjunction with SC 2022: The International Conference for High Performance Computing, Networking, Storage and Analysis
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages21-30
Number of pages10
ISBN (Electronic)9781665475648
DOIs
StatePublished - 2022
Event4th IEEE/ACM Workshop on Programming and Performance Visualization Tools, ProTools 2022 - Dallas, United States
Duration: Nov 13 2022Nov 18 2022

Publication series

NameProceedings of ProTools 2022: Workshop on Programming and Performance Visualization Tools, Held in conjunction with SC 2022: The International Conference for High Performance Computing, Networking, Storage and Analysis

Conference

Conference4th IEEE/ACM Workshop on Programming and Performance Visualization Tools, ProTools 2022
Country/TerritoryUnited States
CityDallas
Period11/13/2211/18/22

Funding

of Science laboratory, is operated under Contract No. DE-AC02-06CH11357. The U.S. Government retains for itself, and others acting on its behalf, a paid-up nonexclusive, irrevocable worldwide license in said article to reproduce, prepare derivative works, distribute copies publicly and display publicly, by or on behalf of the Government. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan. http://energy.gov/downloads/doe-public-access-plan. This work was also supported by the Scientific Discovery through Advanced Computing (SciDAC) program funded by U.S. Department of Energy, Office of Science, Advanced Scientific Computing Research (ASCR) under contract DE-SC0021299.

Keywords

  • Multiphysics application, adaptive mesh refinement, performance, data analysis

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