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Performance Improvements of a Parallel Multithreading Self-gravity Algorithm

  • Nestor RocchettiEmail author
  • Daniel Frascarelli
  • Sergio Nesmachnow
  • Gonzalo Tancredi
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 796)

Abstract

This article presents the application of performance optimization techniques to improve the computational efficiency of a parallel multithreading algorithm for self-gravity calculation on agglomerates. The studied algorithm applies the Discrete Element Method to simulate an ensemble of interacting particles under several contact and body forces. Based on the time scales of the process involved in the problem, we used a computation algorithm that speed up the self-gravity calculation based on defining a mesh over the simulated space. Specific performance improvements are presented, including the update of the occupied regions of the space, profiling and reimplementation of the most time consuming routines. Results indicate that the proposed implementation scale appropriately (almost-linear behavior) with the number of computational resources and the number of particles. The proposed improvements allow accelerating up to 50\(\times \) the execution times over the previous version of the self-gravity algorithm in the studied scenarios.

Notes

Acknowledgments

The work of Néstor Rocchetti, Sergio Nesmachnow, and Gonzalo Tancredi has been partly supported by CSIC, ANII, and PEDECIBA (Uruguay).

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Nestor Rocchetti
    • 1
    Email author
  • Daniel Frascarelli
    • 1
  • Sergio Nesmachnow
    • 1
  • Gonzalo Tancredi
    • 2
  1. 1.Facultad de IngenieríaUniversidad de la RepúblicaMontevideoUruguay
  2. 2.Facultad de CienciasUniversidad de la RepúblicaMontevideoUruguay

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