Parallel optimization of convolution algorithm on multi-core DSP
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(1. College of Computer Science and Technology, National University of Defense Technology, Changsha 410073, China;2. National Key Laboratory of Parallel and Distributed Computing, National University of Defense Technology, Changsha 410073, China)

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TP391

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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.

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XU Jinwei, WANG Qinglin, LI Yalin, JIANG Jingfei, GAO Lei, LI Rongchun, LI Dongsheng. Parallel optimization of convolution algorithm on multi-core DSP[J]. Journal of National University of Defense Technology,2024,46(1):103-112.

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History
  • Received:September 20,2022
  • Revised:
  • Adopted:
  • Online: January 28,2024
  • Published: February 28,2024
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