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A Novel Chaining-Based Indirect Addressing Mode in a Vertical Vector Processor

  • Sven Gesper*
  • , Daniel Köhler
  • , Gia Bao Thieu
  • , Jasper Homann
  • , Frank Meinl
  • , Holger Blume
  • , Guillermo Payá-Vayá
  • *Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference contributionResearchpeer review

Abstract

Efficient processing architectures for irregular data patterns require vector element addressing with flexible indices. Therefore, state-of-the-art SIMD vector extensions implement gather and scatter instructions for indexed addressing of data in memory. In vertical vector processors, different data is processed sequentially in parallel lanes and can be exchanged via chaining. This paper proposes an extension of such chaining mechanisms in a vertical vector processor architecture (V2PRO) to flexibly chain not only data but also address offsets between vector lanes. The indirect addressing enables vector access patterns with irregular strides for both register file and memory. The extension has a low hardware overhead of +4.8 % lookup tables and +1.8% registers on a Xilinx Ultrascale+ FPGA. A runtime evaluation for two applications from computer vision, namely Deformable Convolutions and point cloud encoding with PointPillars, demonstrates speedups of at least an order of magnitude with the proposed extension.

Original languageEnglish
Title of host publicationEmbedded Computer Systems
Subtitle of host publicationArchitectures, Modeling, and Simulation - 24th International Conference, SAMOS 2024, Proceedings
EditorsLuigi Carro, Francesco Regazzoni, Christian Pilato
PublisherSpringer Science and Business Media Deutschland GmbH
Pages167-182
Number of pages16
ISBN (Electronic)978-3-031-78377-7
ISBN (Print)9783031783760
DOIs
Publication statusPublished - 28 Jan 2025
Event24th International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation, SAMOS 2024 - Samos, Greece
Duration: 29 Jun 20244 Jul 2024

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume15226 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference24th International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation, SAMOS 2024
Country/TerritoryGreece
CitySamos
Period29 Jun 20244 Jul 2024

Keywords

  • Computer Vision
  • Indirect Addressing Mode
  • Radar Object Detection
  • Vector Processor Architecture

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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