Cited time in webofscience Cited time in scopus

A 40nm 100Kb 118.44TOPS/W Ternary-weight Computein-Memory RRAM Macro with Voltage-sensing Read and Write Verification for reliable multi-bit RRAM operation

Title
A 40nm 100Kb 118.44TOPS/W Ternary-weight Computein-Memory RRAM Macro with Voltage-sensing Read and Write Verification for reliable multi-bit RRAM operation
Author(s)
Yoon, Jong-HyeokChang, MuyaKhwa, Win-SanChih, Yu-DerChang, Meng-FanRaychowdhury, Arijit
Issued Date
2021-04-29
Citation
IEEE Custom Integrated Circuits Conference (CICC 2021), pp.152 - 153
Type
Conference Paper
ISBN
9781728175812
ISSN
2152-3630
Abstract
RRAM is a promising candidate for compute-in-memory (CIM) applications owing to its natural multiply-and-accumulate (MAC)-supporting structure, high bit-density, non-volatility, and a monolithic CMOS and RRAM process. In particular, multi-bit encoding in RRAM cells helps support advanced applications such as AI with higher MAC throughput and bit-density. Notwithstanding prior efforts into commercializing RRAM technology, underlying challenges hinder the wide usage of RRAM [1]. As a circuit-domain approach to address the challenges, this paper presents a 101.4Kb ternary-weight RRAM macro with 256x256 cells supporting: (1) CIM for ternary weight networks by employing voltage-based read (RD) with active feedback surmounting a low resistance ratio (R-ratio) between the high resistance state (HRS) and the low resistance state (LRS) in high-endurance RRAM, and (2) iterative write with verification (IWR) to facilitate a reliable multi-bit encoding under a narrow margin. Compared to [2] supporting CIM with binary RRAM cells, this work provides 38.44x (=33x3/23x3) flexibility on 3x3 filters in convolutional neural networks (CNNs), and 1.585x bit density improvement, thereby enabling advanced CIM applications with ternary weight networks. © 2021 IEEE.
URI
http://hdl.handle.net/20.500.11750/46936
DOI
10.1109/CICC51472.2021.9431412
Publisher
IEEE Solid-State Circuits Society
Related Researcher
  • 윤종혁 Yoon, Jong-Hyeok
  • Research Interests Artificial intelligence; SLAM; edge intelligence; in-memory computing; multi-standard Ethernet transceiver design
Files in This Item:

There are no files associated with this item.

Appears in Collections:
Department of Electrical Engineering and Computer Science Intelligent Integrated Circuits and Systems Lab 2. Conference Papers

qrcode

  • twitter
  • facebook
  • mendeley

Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE