Analysis of relationship between SIMD-processing features used in NVIDIA GPUs and NEC SX-Aurora TSUBASA vector processors

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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

13 Citations (Scopus)


This paper presents comprehensive analysis of main SIMD-processing features and computational characteristics of three high performance architectures: two NVIDIA GPU architectures (of Pascal and Volta generations) and NEC SX-Aurora TSUBASA vector processor. Since both these types of architectures strongly rely on using SIMD-processing features, certain similarities of data-processing principles can be found between them. However, despite having vectorised data-processing included in both NVIDIA GPU and NEC SX-Aurora TSUBASA architectures, vectorisation features of both architectures are implemented in completely different ways. These differences lead to several fundamental restrictions on classes of algorithms which can be efficiently implemented on corresponding platforms. This paper is devoted to the research of the possibility of porting various classes of programs and algorithms among the discussed architectures with a focus on utilising all vectorisation features available. However, without a detailed analysis of similar and different SIMD-processing features in these architectures, it is impossible to approach this problem. The performed analysis allowed us to identify several important examples of typical applications and algorithms. Some of them demonstrated comparable and the others showed different efficiency on NVIDIA GPUs and NEC SX-Aurora TSUBASA vector processors, including reduction operations, programs relying on frequent indirect memory accesses and data-transfers through co-processor interconnect. Moreover, the conducted analysis allows to easily extend this set of examples to approach the problem of automated porting of programs between the reviewed architectures, what we consider as an important direction of our future research.

Original languageEnglish
Title of host publicationParallel Computing Technologies - 15th International Conference, PaCT 2019, Proceedings
EditorsVictor Malyshkin
PublisherSpringer Verlag
Number of pages15
ISBN (Print)9783030256357
Publication statusPublished - 2019
Event15th International Conference on Parallel Computing Technologies, PaCT 2019 - Almaty, Kazakhstan
Duration: 2019 Aug 192019 Aug 23

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11657 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference15th International Conference on Parallel Computing Technologies, PaCT 2019


  • SIMD
  • Vector processing


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