Big-Computing and Little-Storing STT-MRAM PIM Architecture With Charge Domain Based MAC Operation

  • Yunho Jang
  • , Dongsu Kim
  • , Yeseul Kim
  • , Jongsun Park*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Spin transfer torque magnetic random access memory (STT-MRAM) is a promising memory technology for processing in memory (PIM) thanks to its high endurance and relatively low device-to-device and cycle-to-cycle variations. However, the low OFF/ON ratio of STT device limits the number of active row-lines during multiply-accumulate (MAC) operations, degrading energy efficiency and computation speed. In this paper, we present an energy efficient and high speed Big-computing and Little-storing STT-MRAM PIM (BCLS-SP) architecture, which can increase the number of active row-lines with almost no area overhead. In the BCLS-SP architecture, a charge domain-based STT-MRAM PIM (CD-SP) structure is employed to concurrently activate many row-lines by improving MAC operation reliability. Filter-wise weight compression (FWC) and weight sharing (WS) are also devised to compress the weights stored in CD-SP, thus reducing area cost. In addition, the proposed architecture performs MAC operations with skipping zero-valued input (SZI) and zero-conversion scheme (ZCS) for better energy efficiency and performance. The simulations using 28nm CMOS process show that the BCLS-SP architecture shows energy reduction of 29% and performance improvement of 3.6 compared to the recent memristive device-based PIM using weight compression and input skipping.

Original languageEnglish
Pages (from-to)1239-1252
Number of pages14
JournalIEEE Transactions on Computers
Volume74
Issue number4
DOIs
Publication statusPublished - 2025

Bibliographical note

Publisher Copyright:
© 2024 IEEE. All rights reserved.

Keywords

  • Deep neural network (DNN)
  • input skipping
  • processing in memory (PIM)
  • spin torque transfer magnetic random access memory (STT-MRAM)
  • weight compression

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture
  • Computational Theory and Mathematics

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