Methodology to define a static allocation mapping based on memory access patterns and the Signature of MPI applications in HPC systems

Tools to identify problems and improve MPI applications performance running on an HPC system require information from the application and the system. In this work we will focus on defining a methodology to analyze how memory usage affects an MPI application performance running on this HPC system. This methodology will obtain valid and comparable data based on different memory access patterns that will allow defining key performance values used to characterize the HPC system behavior in front of these access patterns and to characterize the Application Signature behavior, (PAS2P Signature that obtains the representative phases of the MPI application) in front of these same access patterns. With these key performance values, we will be able to detect memory access application problems, suggest improvements and define a mapping policy for this application in this HPC system to improve its performance and to determine limits to these improvements.

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Publication Details

Journal
Journal of Computer Science and Technology
Published
2024-10-18
DOI
https://doi.org/10.24215/16666038.24.e12
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Methodology to define a static allocation mapping based on memory access patterns and the Signature of MPI applications in HPC systems

Eva Bruballa, Dolores Isabel Rexachs, Remo Suppi, Alvaro Wong et al.
Journal of Computer Science and Technology
Parallel Computing and Optimization Techniques
article

Methodology to define a static allocation mapping based on memory access patterns and the Signature of MPI applications in HPC systems

Eva Bruballa, Dolores Isabel Rexachs, Remo Suppi, Alvaro Wong, Emilio Luque, Gerard Enrique
article en

Abstract

Tools to identify problems and improve MPI applications performance running on an HPC system require information from the application and the system. In this work we will focus on defining a methodology to analyze how memory usage affects an MPI application performance running on this HPC system. This methodology will obtain valid and comparable data based on different memory access patterns that will allow defining key performance values used to characterize the HPC system behavior in front of these access patterns and to characterize the Application Signature behavior, (PAS2P Signature that obtains the representative phases of the MPI application) in front of these same access patterns. With these key performance values, we will be able to detect memory access application problems, suggest improvements and define a mapping policy for this application in this HPC system to improve its performance and to determine limits to these improvements.

Journal of Computer Science and TechnologyVol. 24(2)
Universitat Autònoma de Barcelona (ES)
European Regional Development Fund, Agencia Estatal de Investigación
Openalex Percentile: Top 81%
Parallel Computing and Optimization Techniques
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