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Affiliation of Author(s):电子信息工程学院

Title of Paper:Design of multifunctional convolutional neural network accelerator for IoT endpoint SoC

Journal:Lect. Notes Eng. Comput. Sci.

Abstract:Convolutional neural network (CNN) is a machine learning algorithm that plays an important role in image recognition and classification applications. In order to enable the IoT endpoint SoC with limited computing capability to support CNN algorithm, a multifunctional CNN accelerator is proposed which implements major computing components in CNN by hardware. Each computing module is arbitrarily combined by parameter configuration to complete the complex network calculation. In this paper, a SoC with Cortex-M3 kernel is implemented in FPGA as a test platform to verify the performance of the designed accelerator. Evaluation of design scheme is performed by comparing the execute time of the Lenet-5 network on the designed SoC, Intel 7500, Samsung S5P6818 and Allwinner H3. The comparison results show that the compact accelerator proposed in this paper makes the CNN computing power of the SoC based on the Cortex-M3 kernel exceeds the Cortex-A53 kernel, and its CNN computing power per unit frequency reaches 6 times that of the Intel 7500. © 2018 Newswood Limited.

ISSN No.:2078-0958

Translation or Not:no

Date of Publication:2018-01-01

Co-author:Zhang, Yuanyuan,zf,Rehan

Correspondence Author:吴宁