ONNC-based software development platform for configurable NVDLA designs

Wei Fen Lin, Cheng Tao Hsieh, Cheng Yi Chou

研究成果: Conference contribution

2 引文 斯高帕斯(Scopus)

摘要

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.

原文English
主出版物標題2019 International Symposium on VLSI Design, Automation and Test, VLSI-DAT 2019
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9781728106557
DOIs
出版狀態Published - 2019 4月
事件2019 International Symposium on VLSI Design, Automation and Test, VLSI-DAT 2019 - Hsinchu, Taiwan
持續時間: 2019 4月 222019 4月 25

出版系列

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

Conference

Conference2019 International Symposium on VLSI Design, Automation and Test, VLSI-DAT 2019
國家/地區Taiwan
城市Hsinchu
期間19-04-2219-04-25

All Science Journal Classification (ASJC) codes

  • 電氣與電子工程
  • 安全、風險、可靠性和品質
  • 儀器
  • 電腦網路與通信
  • 硬體和架構

指紋

深入研究「ONNC-based software development platform for configurable NVDLA designs」主題。共同形成了獨特的指紋。

引用此