OSA-HCIM: On-The-Fly Saliency-Aware Hybrid SRAM CIM with Dynamic Precision Configuration

Chen, Yung-Chin; Ando, Shimpei; Fujiki, Daichi; Takamaeda-Yamazaki, Shinya; Yoshioka, Kentaro

doi:10.1109/asp-dac58780.2024.10473966

2024 29th Asia and South Pacific Design Automation Conference (ASP-DAC) 2024

DOI: 10.1109/asp-dac58780.2024.10473966

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OSA-HCIM: On-The-Fly Saliency-Aware Hybrid SRAM CIM with Dynamic Precision Configuration

Yung-Chin Chen,

Shimpei Ando,

Daichi Fujiki

et al.

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A review of SRAM-based compute-in-memory circuits

Yoshioka,

Ando,

Miyagi

et al. 2024

Jpn. J. Appl. Phys.

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This paper presents a review of SRAM-based Compute-in-Memory (CIM) circuits, with a focus on both Digital CIM (DCIM) and Analog CIM (ACIM) implementations. We explore the fundamental concepts, architectures, and operational principles of CIM technology. The review compares DCIM and ACIM approaches, examining their respective advantages and challenges. DCIM offers high computational precision and process scaling benefits, while ACIM provides superior power and area efficiency, particularly for medium-precision applications. We analyze various ACIM implementations, including current-based, time-based, and charge-based approaches, with a detailed look at charge-based ACIMs. The paper also discusses emerging hybrid CIM architectures that combine DCIM and ACIM to leverage the strengths of both approaches.

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A review of SRAM-based compute-in-memory circuits

Yoshioka,

Ando,

Miyagi

et al. 2024

Jpn. J. Appl. Phys.

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OSA-HCIM: On-The-Fly Saliency-Aware Hybrid SRAM CIM with Dynamic Precision Configuration

Cited by 1 publication

References 16 publications

A review of SRAM-based compute-in-memory circuits

A review of SRAM-based compute-in-memory circuits

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