Approximate SFQ-Based Computing Architecture Modeling With Device-Level Guidelines

Single-flux-quantum (SFQ) logic has emerged as a promising post-Moore technology thanks to its ultra-fast and lowenergy operation. However, despite progress in various fields, its feasibility is questionable due to the prohibitive cooling cost. Proven conventional ideas, such as approximate computing, may help to resolve this challenge. However, introducing such ideas has been impossible due to the complex performance, power, and error trade-offs originating from the unique SFQ device characteristics. This work introduces approximate SFQ-based computing (AxSFQ) with an architecture modeling framework and essential design guidelines. Our optimized device-level AxSFQ showcases 30˜ 100 times energy efficiency improvement, which motivates further circuit and architecture-level exploration

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Publication Details

Journal
IEEE Computer Architecture Letters
Published
2025-05-26
DOI
https://doi.org/10.1109/lca.2025.3573740
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
Field-Weighted Citation Impact
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Approximate SFQ-Based Computing Architecture Modeling With Device-Level Guidelines

Masamitsu Tanaka, Ilkwon Byun, Teruo Tanimoto, Satoshi Kawakami et al.
1 links
IEEE Computer Architecture Letters
Parallel Computing and Optimization Techniques
article

Approximate SFQ-Based Computing Architecture Modeling With Device-Level Guidelines

Masamitsu Tanaka, Ilkwon Byun, Teruo Tanimoto, Satoshi Kawakami, Koji Inoue, Pratiksha Mundhe, Yuta Hano
article en

Abstract

Single-flux-quantum (SFQ) logic has emerged as a promising post-Moore technology thanks to its ultra-fast and lowenergy operation. However, despite progress in various fields, its feasibility is questionable due to the prohibitive cooling cost. Proven conventional ideas, such as approximate computing, may help to resolve this challenge. However, introducing such ideas has been impossible due to the complex performance, power, and error trade-offs originating from the unique SFQ device characteristics. This work introduces approximate SFQ-based computing (AxSFQ) with an architecture modeling framework and essential design guidelines. Our optimized device-level AxSFQ showcases 30˜ 100 times energy efficiency improvement, which motivates further circuit and architecture-level exploration

IEEE Computer Architecture LettersVol. 24(2)
Kyushu University (JP), Nagoya University (JP)
Industry, innovation and infrastructure
Openalex Percentile: Top 90%
Parallel Computing and Optimization Techniques
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