Low Precision Floating-point Arithmetic for High Performance FPGA-based CNN Acceleration

29 Feb 2020 Wu Chen Wang Mingyu Chu Xinyuan Wang Kun He Lei

Low precision data representation is important to reduce storage size and memory access for convolutional neural networks (CNNs). Yet, existing methods have two major limitations: (1) requiring re-training to maintain accuracy for deep CNNs, and (2) needing 16-bit floating-point or 8-bit fixed-point for a good accuracy... (read more)

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