Booth Fusion: Efficient Bit Fusion Multiplier with Booth Encoding

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초록

Recently, several attempts have been made to optimize Deep Neural Networks (DNNs) through various hardware acceleration methods. Among them, Bit Fusion, the dynamic bit-level fusion/decomposition hardware architecture, was noted. We introduce a new model structure, Booth Fusion, which makes dynamic bit-level operations more efficient by implementing Bit Fusion with booth encoding. Our design shows improvements in 16.4% for the number of LUT and 14.2% for throughput.

키워드

Hardware Accelerators; Quantization; Bit-Level Composability; Bit Fusion; Booth Fusion
제목
Booth Fusion: Efficient Bit Fusion Multiplier with Booth Encoding
저자
Lee, Seokho; Kim, Youngmin
DOI
10.1109/ISOCC50952.2020.9332943
발행일
2020
유형
Proceedings Paper
저널명
2020 17TH INTERNATIONAL SOC DESIGN CONFERENCE (ISOCC 2020)
페이지
73 ~ 74