Implementing VTA, a tensor accelerator on Flow-in-Cloud

Kazuei Hironaka, Kensuke Iizuka, Hideharu Amano

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

Abstract

A multi-FPGA system Flow-in-Cloud (FiC) consists of nodes with a mid-class cost-efficient FPGA and Raspberry Pi3B connected with high speed serial links. It aims to implement a large scale AI applications which is difficult to be implemented on a single FPGA by dividing the target into a number of boards. On the other hand, overlay domain specific architecture receives attention for implementing complicated application programs easily on the FPGA. Here, we focus on an open-source AI compiler framework Apache TVM, and its implementation for FPGA, VTA(Versatile Tensor Accelerator). In order to use FiC through the TVM, we implemented it on FiC and executed the ResNet-18 inference benchmark. The preliminary evaluation results showed that VTA on FiC-SW achieved up to 10 times performance compared to the execution on ARM Cortex-A54 software.

Original languageEnglish
Title of host publicationProceedings - 8th International Conference on Applied Computing and Information Technology, ACIT 2021
PublisherAssociation for Computing Machinery
Pages46-50
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

  • Apache TVM
  • FPGA
  • Versatile Tensor Acclerator

ASJC Scopus subject areas

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

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