Abstract:<p>Deep convolutional neural networks (CNNs) generate intensive inter-layer data during inference, which results in substantial on-chip memory size and off-chip bandwidth. To solve the memory constraint, this paper proposes an accelerator adopted with a compression technique that can reduce the inter-layer data by removing both intra- and inter-channel redundant information. Principal component analysis (PCA) is utilized in the compression process to concentrate inter-channel information. The spatial dif… Show more
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