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A CNN Accelerator with Embedded Risc-V Controllers

  • Zhejiang University

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

Abstract

Convolutional Neural Network is a promising technology in machine learning. Due to its vast computing and data requirements, it needs to be run with a specific accelerator to achieve reasonable energy efficiency. Improving the performance of accelerators has become the research hotspot. A mixed-precision structure can be used to improve hardware utilization, thus reducing area and power. However, the mixed-precision flow control is so complicated that it costs too much hardware resources. In this paper, a CNN accelerator with embedded RISC-V controllers is introduced to achieve flexible control at a very low cost. The ASIC synthesized results show that the proposed design area with two embedded cores is 5% less than the basic design.

Original languageEnglish
Title of host publicationChina Semiconductor Technology International Conference 2021, CSTIC 2021
EditorsCor Claeys, Steve X. Liang, Qinghuang Lin, Ru Huang, Hanming Wu, Peilin Song, Linyong Pang, Ying Zhang, Beichao Zhang, Xinping Xinping Qu, Cheng Zhuo, Hsiang-Lan Lung
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665449458
DOIs
StatePublished - 14 Mar 2021
Externally publishedYes
Event2021 China Semiconductor Technology International Conference, CSTIC 2021 - Shanghai, China
Duration: 14 Mar 202115 Mar 2021

Publication series

NameChina Semiconductor Technology International Conference 2021, CSTIC 2021

Conference

Conference2021 China Semiconductor Technology International Conference, CSTIC 2021
Country/TerritoryChina
CityShanghai
Period14/03/2115/03/21

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

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