A 639.38GOPS Hybrid-Domain Logic-Compatible Multi-Level Embedded Flash Computing-in-Memory Macro with Spike-Edge Computation

Jiho Chun, Edward Choi, Byeongseon Choi, Donghyeon Yi, Sohmyung Ha, Ik Joon Chang, Minkyu Je

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Computing in Memory (CIM) has emerged as a promising research field, significantly reducing power consumption and latency associated with massive data movement and multiply-and-accumulate (MAC) operations in edge Al devices. For battery-constrained edge devices, non-volatile memories (NVMs) are ideal due to their ability to retain neural network parameters even when powered down, ensuring rapid response time upon device wake-up. Recent studies [2, 3] have integrated NVM into CIM architectures using STT-MRAM and RRAM, achieving high throughput and energy efficiency. Nevertheless, NVMs necessitate specialized fabrication technologies and additional manufacturing steps, which increase process complexity and costs (Fig. 1 (top-left)). As NVM processes advance, these technologies become increasingly challenging to access due to the escalating costs.

Original languageEnglish (US)
Title of host publication2024 IEEE Asian Solid-State Circuits Conference, A-SSCC 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350376326
DOIs
StatePublished - 2024
Event2024 IEEE Asian Solid-State Circuits Conference, A-SSCC 2024 - Hiroshima, Japan
Duration: Nov 18 2024Nov 21 2024

Publication series

Name2024 IEEE Asian Solid-State Circuits Conference, A-SSCC 2024

Conference

Conference2024 IEEE Asian Solid-State Circuits Conference, A-SSCC 2024
Country/TerritoryJapan
CityHiroshima
Period11/18/2411/21/24

ASJC Scopus subject areas

  • Hardware and Architecture
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Control and Optimization

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