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Parallel Performance Engineering using Score-P and Vampir

Published: 15 April 2023 Publication History

Abstract

This tutorial will introduce participants to the Score-P measurement system and the Vampir trace visualization tool for performance analysis. We will provide examples and hands-on exercises covering the full performance engineering workflow cycle on applications that include MPI, OpenMP, and GPU parallelism. Users will learn the following concepts: 1. How to collect an initial profile of their code with Score-P. 2. Evaluation of that profile and its associated measurement overhead. 3. The concepts of scoring and filtering a profile and measurement respectively. 4. How to control the Score-P measurement system via environment variables. 5. How to collect useful traces with acceptable overhead. 6. How to understand trace visualization in Vampir.

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Andreas Gocht, Robert Schöne, and Jan Frenzel. 2020. Advanced Python Per- formance Monitoring with Score-P. Tools for High Performance Computing 2018 / 2019 (Oct. 2020), 261--270. https://doi.org/10.1007/978--3-030--66057--4_14 arXiv:2010.15444 [cs.DC]
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cover image ACM Conferences
ICPE '23 Companion: Companion of the 2023 ACM/SPEC International Conference on Performance Engineering
April 2023
421 pages
ISBN:9798400700729
DOI:10.1145/3578245
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 15 April 2023

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Author Tags

  1. high performance computing
  2. measurement
  3. performance engineering
  4. visualization

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