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Parallelization of All-Pairs-Shortest-Path Algorithms in Unweighted Graph

Authors:

Masahiro Nakao,

Mitsuhisa SatoAuthors Info & Claims

HPCAsia '20: Proceedings of the International Conference on High Performance Computing in Asia-Pacific Region

Pages 63 - 72

https://doi.org/10.1145/3368474.3368478

Published: 15 January 2020 Publication History

Abstract

The design of the network topology of a large-scale parallel computer system can be represented as an order/degree problem in graph theory. To solve the order/degree problem, it is necessary to obtain an all-pairs-shortest-path (APSP) of the graph. Thus, this paper evaluates two parallel algorithms that quickly find the APSP in unweighted graphs and compares their performance. The first APSP algorithm is based on the breadth-first search (BFS-APSP) and the second is based on the adjacency matrix (ADJ-APSP). First, we develop serial algorithms and threaded algorithms using OpenMP, and show that ADJ-APSP is up to 32.34 times faster than BFS-APSP. Next, we develop hybrid-parallel algorithms using OpenMP and MPI, and show that BFS-APSP is faster than ADJ-APSP under certain conditions because the maximum number of processes in BFS-APSP is greater than in ADJ-APSP. In addition, we parallelize ADJ-APSP using a single GPU (NVIDIA Tesla V100) and achieve a speed increase of up to 16.53-fold compared to that of a single CPU. Finally, we evaluate the performance of the algorithms using 128 GPUs and achieve a computation time 101.10 times faster than that using a single GPU. Moreover, it is shown that the calculation time of both algorithms can be greatly reduced when the input graphs are symmetric.

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Cited By

Alghamdi MHe LRen SMaray M(2024)Efficient Parallel Processing of All-Pairs Shortest Paths on Multicore and GPU SystemsIEEE Transactions on Consumer Electronics10.1109/TCE.2023.332732870:1(2896-2908)Online publication date: Feb-2024
https://doi.org/10.1109/TCE.2023.3327328
Komilov MNishanov AAllamov OKhalmurotov OErkinjon ASadullayev NAllamova S(2023)The method which works in parallel and distributed into a large-scale graph in the regulation of vehicle movementPROBLEMS IN THE TEXTILE AND LIGHT INDUSTRY IN THE CONTEXT OF INTEGRATION OF SCIENCE AND INDUSTRY AND WAYS TO SOLVE THEM: (PTLICISIWS-2022)10.1063/5.0145688(040101)Online publication date: 2023
https://doi.org/10.1063/5.0145688
Nakao MTsukamoto MHanada YYamamoto K(2022)Graph optimization algorithm using symmetry and host bias for low-latency indirect networkParallel Computing10.1016/j.parco.2022.102983114:COnline publication date: 1-Dec-2022
https://dl.acm.org/doi/10.1016/j.parco.2022.102983
Show More Cited By

Index Terms

Parallelization of All-Pairs-Shortest-Path Algorithms in Unweighted Graph
1. Theory of computation
  1. Design and analysis of algorithms
    1. Parallel algorithms
      1. Massively parallel algorithms

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cover image ACM Other conferences

HPCAsia '20: Proceedings of the International Conference on High Performance Computing in Asia-Pacific Region

January 2020

247 pages

ISBN:9781450372367

DOI:10.1145/3368474

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 15 January 2020

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HPCAsia2020

HPCAsia2020: International Conference on High Performance Computing in Asia-Pacific Region

January 15 - 17, 2020

Fukuoka, Japan

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Cited By

Alghamdi MHe LRen SMaray M(2024)Efficient Parallel Processing of All-Pairs Shortest Paths on Multicore and GPU SystemsIEEE Transactions on Consumer Electronics10.1109/TCE.2023.332732870:1(2896-2908)Online publication date: Feb-2024
https://doi.org/10.1109/TCE.2023.3327328
Komilov MNishanov AAllamov OKhalmurotov OErkinjon ASadullayev NAllamova S(2023)The method which works in parallel and distributed into a large-scale graph in the regulation of vehicle movementPROBLEMS IN THE TEXTILE AND LIGHT INDUSTRY IN THE CONTEXT OF INTEGRATION OF SCIENCE AND INDUSTRY AND WAYS TO SOLVE THEM: (PTLICISIWS-2022)10.1063/5.0145688(040101)Online publication date: 2023
https://doi.org/10.1063/5.0145688
Nakao MTsukamoto MHanada YYamamoto K(2022)Graph optimization algorithm using symmetry and host bias for low-latency indirect networkParallel Computing10.1016/j.parco.2022.102983114:COnline publication date: 1-Dec-2022
https://dl.acm.org/doi/10.1016/j.parco.2022.102983
Kawano RMatsutani HKoibuchi MAmano H(2021)GPU Parallelization of All-Pairs-Shortest-Path Algorithm in Low-Degree Unweighted Regular GraphProceedings of the the 8th International Virtual Conference on Applied Computing & Information Technology10.1145/3468081.3471122(51-55)Online publication date: 20-Jun-2021
https://dl.acm.org/doi/10.1145/3468081.3471122
Nakao MTsukamoto MHanada YYamamoto K(undefined)Graph Optimization Algorithm Using Symmetry and Host Bias for Low-Latency Indirect NetworkSSRN Electronic Journal10.2139/ssrn.4048955
https://doi.org/10.2139/ssrn.4048955

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