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Integration of Modern HPC Performance Tools in Vlasiator for Exascale Analysis and Optimization

Coti, Camille (author)
École de Technologie Supérieure Montréal, Québec, Canada
Pfau-Kempf, Yann (author)
University of Helsinki Helsinki, Finland
Battarbee, Markus (author)
University of Helsinki
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Ganse, Urs (author)
University of Helsinki Helsinki, Finland
Shende, Sameer (author)
University of Oregon Eugene, Oregon, USA
Huck, Kevin (author)
University of Oregon Eugene, Oregon, USA
Rodriquez, Jordi (author)
University of Oregon Eugene, Oregon, USA
Kotipalo, Leo (author)
University of Helsinki Helsinki, Finland
Faj, Jennifer (author)
KTH,Beräkningsvetenskap och beräkningsteknik (CST)
Williams, Jeremy J. (author)
KTH,Beräkningsvetenskap och beräkningsteknik (CST)
Peng, Ivy Bo (author)
KTH,Beräkningsvetenskap och beräkningsteknik (CST)
Malony, Allen D. (author)
University of Oregon Eugene, Oregon, USA
Markidis, Stefano (author)
KTH,Beräkningsvetenskap och beräkningsteknik (CST)
Palmroth, Minna (author)
University of Helsinki Helsinki, Finland; Finnish Meteorological Institute Helsinki, Finland
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 (creator_code:org_t)
2024
2024
English.
In: IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), May 27-31, San Francisco, California, USA.. - 9798350364606
  • Conference paper (peer-reviewed)
Abstract Subject headings
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  • Key to the success of developing high-performance applications for present and future heterogeneous supercomputers will be the systematic use of measurement and analysis to understand factors that affect delivered performance in the context of parallelization strategy, heterogeneous programming methodology, data partitioning, and scalable algorithm design. The evolving complexity of future exascale platforms makes it unrealistic for application teams to implement their own tools. Similarly, it is naive to expect available robust performance tools to work effectively out-of-the-box, without integration and specialization in respect to application-specific requirements and knowledge. Vlasiator is a powerful massively parallel code for accurate magnetospheric and solar wind plasma simulations. It is being ported to the LUMI HPC system for advanced modeling of the Earth’s magnetosphere and surrounding solar wind. Building on a preexisting Vlasiator performance API called Phiprof, our work significantly advances the performance measurement and analysis capabilities offered to Vlasiator using the TAU, APEX, and IPM tools. The results presented show in-depth characterization of node-level CPU/GPU and MPI communications performance. We highlight the integration of high-level Phiprof events with detailed performance data to expose opportunities for performance tuning. Our results provide important insights to optimize Vlasiator for the upcoming Exascale machines.

Subject headings

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Datorsystem (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Computer Systems (hsv//eng)

Keyword

Compiler and Tools for Parallel Programming
System and Performance Monitoring
Extreme-scale Algorithms
Performance Measurement
Performance Tools and Simulators
Datalogi
Computer Science

Publication and Content Type

ref (subject category)
kon (subject category)

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