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A Novel Algorithm for Bi-objective Performance-Energy Optimization of Applications with Continuous Performance and Linear Energy Profiles on Heterogeneous HPC Platforms

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Euro-Par 2021: Parallel Processing Workshops (Euro-Par 2021)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13098))

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Abstract

Performance and energy are the two most important objectives for optimization on heterogeneous HPC platforms. This work studies a mathematical problem motivated by the bi-objective optimization of a matrix multiplication application on such platforms for performance and energy. We formulate the problem and propose an algorithm of polynomial complexity solving the problem where all the application profiles of objective type one are continuous and strictly increasing, and all the application profiles of objective type two are linear increasing. We solve the problem for the matrix multiplication application employing five heterogeneous processors that include two Intel multicore CPUs, an Nvidia K40c GPU, an Nvidia P100 PCIe GPU, and an Intel Xeon Phi. Based on our experiments, a dynamic energy saving of 17% is gained while tolerating a performance degradation of 5% (a saving of 106 J for an execution time increase of 0.05 s).

This publication has emanated from research conducted with the financial support of Science Foundation Ireland (SFI) under Grant Number 14/IA/2474.

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Author information

Authors and Affiliations

  1. School of Computing, University of Portsmouth, Portsmouth, UK

    Hamidreza Khaleghzadeh

  2. School of Computer Science, University College Dublin, Belfield, Dublin 4, Ireland

    Ravi Reddy Manumachu & Alexey Lastovetsky

Authors
  1. Hamidreza Khaleghzadeh
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  2. Ravi Reddy Manumachu
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  3. Alexey Lastovetsky
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Corresponding author

Correspondence to Ravi Reddy Manumachu .

Editor information

Editors and Affiliations

  1. University of Lisbon, Lisbon, Portugal

    Ricardo Chaves

  2. Department of Computer Engineering, CiTIUS, University of Santiago de Compostela, Santiago de Compostela, La Coruña, Spain

    Dora B. Heras

  3. University of Lisbon, Lisbon, Portugal

    Aleksandar Ilic

  4. Koç University, Istanbul, Turkey

    Didem Unat

  5. Barcelona Supercomputing Center, Barcelona, Spain

    Rosa M. Badia

  6. University of Stirling, Stirling, UK

    Andrea Bracciali

  7. Louisiana State University, Baton Rouge, USA

    Patrick Diehl

  8. Mathematics and Computer Science, Argonne National Laboratory, Lemont, IL, USA

    Anshu Dubey

  9. Ajou University, Suwon, Korea (Republic of)

    Oh Sangyoon

  10. Tennessee Technological University, Cookeville, TN, USA

    Stephen L. Scott

  11. University of Pisa, Pisa, Italy

    Laura Ricci

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Khaleghzadeh, H., Manumachu, R.R., Lastovetsky, A. (2022). A Novel Algorithm for Bi-objective Performance-Energy Optimization of Applications with Continuous Performance and Linear Energy Profiles on Heterogeneous HPC Platforms. In: Chaves, R., et al. Euro-Par 2021: Parallel Processing Workshops. Euro-Par 2021. Lecture Notes in Computer Science, vol 13098. Springer, Cham. https://doi.org/10.1007/978-3-031-06156-1_14

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  • DOI: https://doi.org/10.1007/978-3-031-06156-1_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-06155-4

  • Online ISBN: 978-3-031-06156-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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