Fast 6T SRAM Bit-Line Computing with Consecutive Short Pulse Word-Lines and Skewed Inverter

Jinho Jeong, Jongsun Park

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

Abstract

To overcome the von-Neumann bottleneck, static random-Access memory (SRAM)-based in-memory computing (IMC) which enables parallel data processing in the memory, is being researched. To prevent the read disturbance issue, conventional 6T SRAM IMC employs Word-Line Under-Drive (WLUD), which leads to slow bit-line (BL) computing. Another approach to cope with the read disturbance is to use 10T SRAM cells in which BLs are decoupled for read and write operation. However, the overhead in the bit-cell array density is not affordable. In this paper, a fast 6T SRAM BL computing technique that prevents the read disturbance issue is proposed. The proposed technique adopts two consecutive short pulse WLs to avoid read disturbance, and skewed-inverter-based sense amplifiers to achieve the fast BL computation. A feedback loop for faster BL computing is also proposed. 128 × 128 IMC architecture is implemented using a 28nm CMOS process, and the delay of BL computing is improved 0.354X compared to WLUD in the worst case.

Original languageEnglish
Title of host publicationProceedings - International SoC Design Conference, ISOCC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages292-293
Number of pages2
ISBN (Electronic)9781728183312
DOIs
Publication statusPublished - 2020 Oct 21
Event17th International System-on-Chip Design Conference, ISOCC 2020 - Yeosu, Korea, Republic of
Duration: 2020 Oct 212020 Oct 24

Publication series

NameProceedings - International SoC Design Conference, ISOCC 2020

Conference

Conference17th International System-on-Chip Design Conference, ISOCC 2020
CountryKorea, Republic of
CityYeosu
Period20/10/2120/10/24

Keywords

  • Bitline Computing
  • In-Memory Computing
  • Read Disturb
  • Short Pulse WL

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Instrumentation
  • Artificial Intelligence
  • Hardware and Architecture

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