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Booth Fusion: Efficient Bit Fusion Multiplier with Booth Encoding
- Lee, Seokho;
- Kim, Youngmin
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3초록
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
- 발행일
- 2020
- 유형
- Proceedings Paper
- 저널명
- 2020 17TH INTERNATIONAL SOC DESIGN CONFERENCE (ISOCC 2020)
- 페이지
- 73 ~ 74
- 언어
- ENG
- 출판사
- IEEE
- 발행국가
- 미국
- 분량
- 2 페이지
- ISSN
- P 2163-9612