research-article

Better Process Mapping and Sparse Quadratic Assignment

Authors:

Konrad Von Kirchbach,

Christian Schulz,

Jesper Larsson TräffAuthors Info & Claims

Journal of Experimental Algorithmics (JEA), Volume 25

Article No.: 1.11, Pages 1 - 19

https://doi.org/10.1145/3409667

Published: 30 September 2020 Publication History

Abstract

Communication and topology-aware process mapping is a powerful approach to reduce communication time in parallel applications with known communication patterns on large, distributed memory systems. We address the problem as a quadratic assignment problem (QAP) and present algorithms to construct initial mappings of processes to processors and fast local search algorithms to further improve the mappings. By exploiting assumptions that typically hold for applications and modern supercomputer systems such as sparse communication patterns and hierarchically organized communication systems, we obtain significantly more powerful algorithms for these special QAPs. Our multilevel construction algorithms employ perfectly balanced graph partitioning techniques and exploit the given communication system hierarchy in significant ways. We present improvements to a local search algorithm of Brandfass et al. (2013) and further decrease the running time by reducing the time needed to perform swaps in the assignment as well as by carefully constraining local search neighborhoods. We also investigate different algorithms to create the communication graph that is mapped onto the processor network. Experiments indicate that our algorithms not only dramatically speed up local search but also, due to the multilevel approach, find much better solutions in practice.

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Cited By

Jeannot E(2022)Process mapping on any topology with TopoMatchJournal of Parallel and Distributed Computing10.1016/j.jpdc.2022.08.002170(39-52)Online publication date: Dec-2022
https://doi.org/10.1016/j.jpdc.2022.08.002
Predari MTzovas CSchulz CMeyerhenke H(2021)An MPI-based Algorithm for Mapping Complex Networks onto Hierarchical ArchitecturesEuro-Par 2021: Parallel Processing10.1007/978-3-030-85665-6_11(167-182)Online publication date: 1-Sep-2021
https://dl.acm.org/doi/10.1007/978-3-030-85665-6_11

Index Terms

Better Process Mapping and Sparse Quadratic Assignment
1. Mathematics of computing
  1. Discrete mathematics
    1. Combinatorics
      1. Combinatorial optimization
    2. Graph theory
      1. Graph algorithms

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Published In

cover image ACM Journal of Experimental Algorithmics

ACM Journal of Experimental Algorithmics Volume 25, Issue

Special Issue ALENEX 2018 and Regular Papers

2020

313 pages

ISSN:1084-6654

EISSN:1084-6654

DOI:10.1145/3388470

Issue’s Table of Contents

Copyright © 2020 ACM.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 30 September 2020

Accepted: 01 July 2020

Revised: 01 February 2020

Received: 01 July 2019

Published in JEA Volume 25

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Cited By

Jeannot E(2022)Process mapping on any topology with TopoMatchJournal of Parallel and Distributed Computing10.1016/j.jpdc.2022.08.002170(39-52)Online publication date: Dec-2022
https://doi.org/10.1016/j.jpdc.2022.08.002
Predari MTzovas CSchulz CMeyerhenke H(2021)An MPI-based Algorithm for Mapping Complex Networks onto Hierarchical ArchitecturesEuro-Par 2021: Parallel Processing10.1007/978-3-030-85665-6_11(167-182)Online publication date: 1-Sep-2021
https://dl.acm.org/doi/10.1007/978-3-030-85665-6_11

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