ONNC-based software development platform for configurable NVDLA designs

Wei Fen Lin, Cheng Tao Hsieh, Cheng Yi Chou

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

1 Citation (Scopus)

Abstract

With the proliferation of deep learning and the increasing pressure to deploy inference applications at the edge, many AI chip makers integrate the open source NVIDIA Deep Learning Accelerator (NVDLA) design in their AI solutions. Lack of open source compiler support and having only limited configurability support in the software stacks erect a barrier for developers to freely explore the NVDLA design space at system level. This paper presents an ONNC-based software development platform that includes the first open source compiler for NVDLA-based designs, a virtual platform with various CPU models as well as configurable NVDLA models, and auxiliary tools for debugging. The platform is tightly coupled with the hardware design tradeoffs and provides extendibility for compiler optimization, more CPU types, and more NVDLA hardware configurations. It lifts many restrictions of software development for those who like to leverage the NVDLA design in inference applications.

Original languageEnglish
Title of host publication2019 International Symposium on VLSI Design, Automation and Test, VLSI-DAT 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728106557
DOIs
Publication statusPublished - 2019 Apr
Event2019 International Symposium on VLSI Design, Automation and Test, VLSI-DAT 2019 - Hsinchu, Taiwan
Duration: 2019 Apr 222019 Apr 25

Publication series

Name2019 International Symposium on VLSI Design, Automation and Test, VLSI-DAT 2019

Conference

Conference2019 International Symposium on VLSI Design, Automation and Test, VLSI-DAT 2019
CountryTaiwan
CityHsinchu
Period19-04-2219-04-25

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Safety, Risk, Reliability and Quality
  • Instrumentation
  • Computer Networks and Communications
  • Hardware and Architecture

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