An efficient full-size convolutional computing method based on memristor crossbar
Jinpei Tan,
Siyuan Shen,
Shukai Duan
et al.
Abstract:Modern artificial intelligence systems based on neural networks need to perform a large number of repeated parallel operations quickly. Without hardware acceleration, they cannot achieve effectiveness and availability. Memristor-based neuromorphic computing systems are one of the promising hardware acceleration strategies. In this paper, we propose a full-size convolution algorithm (FSCA) for the memristor crossbar, which can store both the input matrix and the convolution kernel and map the convolution kernel… Show more
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