IMFlexCom: Energy efficient in-memory flexible computing using dual-mode sot-MRAM

Farhana Parveen, Shaahin Angizi, Deliang Fan

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


In this article, we propose an In-Memory Flexible Computing platform (IMFlexCom) using a novel Spin Orbit Torque Magnetic Random Access Memory (SOT-MRAM) array architecture, which could work in dual mode: memory mode and computing mode. Such intrinsic in-memory logic (AND/OR/XOR) could be used to process data within memory to greatly reduce power-hungry and long distance massive data communication in conventional Von Neumann computing systems. A comprehensive reliability analysis is performed, which confirms ∼ 90mV and ∼ 10mV (worst-case) sense margin for memory and in-memory logic operation in variations on resistance-area product and tunnel magnetoresistance. We further show that sense margin for in-memory logic computation can be significantly increased by increasing the oxide thickness. Furthermore, we employ bulk bitwise vector operation and data encryption engine as case studies to investigate the performance of our proposed design. IMFlexCom shows ∼ 35× energy saving and ∼ 18× speedup for bulk bitwise in-memory vector AND/OR operation compared to DRAM-based in-memory logic. Again, IMFlexCom can achieve 77.27% and 85.4% lower energy consumption compared to CMOS-ASIC- and CMOL-based Advanced Encryption Standard (AES) implementations, respectively. It offers almost similar energy consumption as recent DW-AES implementation with 66.7% less area overhead.

Original languageEnglish (US)
Article number36
JournalACM Journal on Emerging Technologies in Computing Systems
Issue number3
StatePublished - Oct 2018
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture
  • Electrical and Electronic Engineering


  • Giant spin Hall effect
  • In-memory computing
  • Magnetic tunnel junction
  • Memory architecture


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