Variable Precision Multiplier for CNN Accelerators Based on Booth Algorithm
Duck-Hyun Guem,
Sunhee Kim
Abstract:As the utilization of CNN increases, many studies on lightweight, such as pruning, quantization, and compression, have been conducted to use CNN models in servers and edge devices. Studies have revealed that quantization greatly reduces the complexity of CNN models while lowering accuracy to a negligible level. CNN models with bit precision lowered from the existing 64/32 floating point to 16, 8, and 4 fixed points are being announced. Therefore, this paper proposes a variable precision multiplier that can sel… Show more
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