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Publishing Language: Chinese | Open Access

Parallel optimization of convolution algorithm on multi-core DSP

Jinwei XU1,2Qinglin WANG1,2Yalin LI1,2Jingfei JIANG1,2Lei GAO1,2Rongchun LI1,2( )Dongsheng LI1,2
College of Computer Science and Technology, National University of Defense Technology, Changsha 410073, China
National Key Laboratory of Parallel and Distributed Computing, National University of Defense Technology, Changsha 410073, China
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Abstract

According to the characteristics of the heterogeneous multi-core DSP (digital signal processing) chip independently developed by National University of Defense Technology and the characteristics of the convolution algorithm, a high-performance multi-core parallel convolution implementation scheme for multi-core DSP architecture was proposed. A feature graph level multi-core parallel scheme is proposed for 1 × 1 convolution. For convolutions with kernels larger than 1, a window level multi-core parallel optimization design was proposed, and an element-wise vectorization based intra-core parallel optimization implementation was proposed. The experimental results show that the proposed parallel optimization method can reach a maximum single core computing efficiency of 64.95%. When the bandwidth is limited, the parallel expansion efficiency of multi-core can still reach 48.36% ~ 88.52%. Compared with E5-2640 CPU, the execution performance on the typical network ResNet50 achieves 5.39x performance acceleration.

CLC number: TP391 Document code: A Article ID: 1001-2486(2024)01-103-10

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Journal of National University of Defense Technology
Pages 103-112

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Cite this article:
XU J, WANG Q, LI Y, et al. Parallel optimization of convolution algorithm on multi-core DSP. Journal of National University of Defense Technology, 2024, 46(1): 103-112. https://doi.org/10.11887/j.cn.202401011

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Received: 20 September 2022
Published: 28 February 2024
© 2024 Journal of National University of Defense Technology

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).