Developing an efficient vector-friendly implementation of the breadth-first search algorithm for NEC SX-aurora tsubasa

Ilya V. Afanasyev, Vladimir V. Voevodin, Kazuhiko Komatsu, Hiroaki Kobayashi

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

Abstract

Breadth-First Search (BFS) is an important computational kernel used as a building-block for many other graph algorithms. Different algorithms and implementation approaches aimed to solve the BFS problem have been proposed so far for various computational platforms, with the direction-optimizing algorithm being the fastest and the most computationally efficient for many real-world graph types. However, straightforward implementation of direction-optimizing BFS for vector computers can be extremely challenging and inefficient due to the high irregularity of graph data structure and the algorithm itself. This paper describes the world’s first attempt aimed to create an efficient vector-friendly BFS implementation of the direction-optimizing algorithm for NEC SX-Aurora TSUBASA architecture. SX-Aurora TSUBASA vector processors provide high-performance computational power together with a world-highest bandwidth memory, making it a very interesting platform for solving various graph-processing problems. The implementation proposed in this paper significantly outperforms the existing state-of-the-art implementations both for modern CPUs (Intel Skylake) and NVIDIA V100 GPUs. In addition, the proposed implementation achieves significantly higher energy efficiency compared to other platforms and implementations both in terms of average power consumption and achieved performance per watt.

Original languageEnglish
Title of host publicationParallel Computational Technologies - 14th International Conference, PCT 2020, Revised Selected Papers
EditorsLeonid Sokolinsky, Mikhail Zymbler
PublisherSpringer
Pages131-145
Number of pages15
ISBN (Print)9783030553258
DOIs
Publication statusPublished - 2020
Event14th International Scientific Conference on Parallel Computational Technologies, PCT 2020 - Perm, Russian Federation
Duration: 2020 May 272020 May 29

Publication series

NameCommunications in Computer and Information Science
Volume1263 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference14th International Scientific Conference on Parallel Computational Technologies, PCT 2020
CountryRussian Federation
CityPerm
Period20/5/2720/5/29

Keywords

  • Breadth-First Search
  • Graph algorithms
  • NEC SX-Aurora TSUBASA
  • Vectorisation

ASJC Scopus subject areas

  • Computer Science(all)
  • Mathematics(all)

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