P3S: A Methodology to Analyze and Predict Application Scalability

Javier Panadero, Alvaro Wong, Dolores Rexachs, Emilio Luque

Research output: Contribution to journalArticleResearchpeer-review

3 Citations (Scopus)

Abstract

© 2017 IEEE. Executing message-passing parallel applications on a large number of resources in an efficient way is not a trivial task. Due to the complex interaction between the parallel applications and the HPC system, many applications may suffer performance inefficiencies when they scale. To achieve an efficient use of these large-scale systems using thousands of cores, a point to consider before executing an application is to know its behavior in the system. In this work, we propose a novel methodology called P3S (Prediction of Parallel Program Scalability), which allows us to analyze and predict the scalability of message-passing applications on a given system. The methodology strives to use a bounded analysis time, and a reduced set of resources to predict the application behavior for large-scale. The experimental validation proves that the P3S is able to predict the application scalability with an average accuracy greater than 95 percent using a reduced set of resources.
Original languageEnglish
Article number8068239
Pages (from-to)642-658
JournalIEEE Transactions on Parallel and Distributed Systems
Volume29
Issue number3
DOIs
Publication statusPublished - 1 Mar 2018

Keywords

  • HPC systems
  • MPI application
  • prediction of an application scalability
  • scalability prediction

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