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摘要:The advancements of neural networks have significantly improved the accuracy of a variety of intelligent applications, such as image processing, voice recognition and so on. However, one of the challenges is to accelerate the speed of inference with the networks designed to be deeper. In this paper, we first realize the algorithm involved in software. Then, combined with the expanded characteristic of RISC-V architecture, the acceleration of convolution operation taking up the largest proportion of computation in CNN is realized by coprocessor expansion mode on open-source Hummingbird E203 processor. Through tests, convolution coprocessor improves the performance of CNN while ensuring the accuracy in function. Finally, the Cifar-10 image classification, a common benchmark in machine learning, is used to verify the feasibility in functions and comparatively analysis the pure software-based and coprocessorbased implementations.
会议名称:

The 2nd International Conference on Artificial Intelligence and Computer Science (AICS 2020)

会议时间:

2020-07-25

会议地点:

中国湖北武汉

  • 专辑:

    信息科技

  • 专题:

    计算机硬件技术; 自动化技术

  • DOI:

    10.26914/c.cnkihy.2020.028954

  • 分类号:

    TP183;TP332

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