GPU Parallelization of All-Pairs-Shortest-Path Algorithm in Low-Degree Unweighted Regular Graph

Ryuta Kawano, Hiroki Matsutani, Michihiro Koibuchi, Hideharu Amano

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The design of the network topology of a large-scale parallel computer system can be represented as an order/degree problem in the graph theory. To solve the order/degree problem, we have to obtain all-pairs-shortest-path (APSP) for the graph. A conventional APSP algorithm for GPUs is based on the adjacency matrix (ADJ-APSP). When focusing on low-degree and unweighted graphs, most of the matrix elements are zero in the first few iterations of the algorithm. We will further speed up the APSP algorithm by treating the adjacency matrix as a sparse matrix in the first iterations of the algorithm. Evaluation results show that our proposed algorithm on a single GPU (NVIDIA GeForce RTX 3080) reduces the execution time by up to 32.7 % compared to the conventional algorithm.

Original languageEnglish
Title of host publicationProceedings - 8th International Conference on Applied Computing and Information Technology, ACIT 2021
PublisherAssociation for Computing Machinery
Pages51-55
Number of pages5
ISBN (Electronic)9781450384933
DOIs
Publication statusPublished - 2021 Jun 20
Event8th International Conference on Applied Computing and Information Technology, ACIT 2021 - Kanazawa, Japan
Duration: 2021 Jun 202021 Jun 22

Publication series

NameACM International Conference Proceeding Series

Conference

Conference8th International Conference on Applied Computing and Information Technology, ACIT 2021
Country/TerritoryJapan
CityKanazawa
Period21/6/2021/6/22

Keywords

  • GPU
  • network topology
  • shortest path algorithm

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

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