Paper Info
Title
Modeling and design optimization of ReRAM
Abstract
Resistive switching memories (ReRAM) have been widely studied for applications in next-generation data storage and neurormorphic computing systems. To enable device-circuit-system co-design and optimization, a SPICE model of ReRAM that can reproduce the device characteristics in circuit simulations is needed. In this paper, we present a novel tool for ReRAM design including a physics-based SPICE model, the model parameters extraction strategy, as well as the system assessment method. This physics-based SPICE model can capture all the essential features of HfOx-based ReRAM including the DC/AC and multi-level switching behaviors, switching reliability, and intrinsic device variations. A strategy is developed to extract the critical model parameters from the fabricated ReRAM devices. A variety of electrical measurements on various ReRAMs are performed to verify and calibrate the model. The assessment method based on the experimentally verified SPICE model can be applied to explore a wide range of applications including: 1) variation-aware and reliability-emphasized system design; 2) system performance evaluation; 3) array architecture optimization. This verified design tool not only enables system design but also enables system optimization that capitalizes on device/circuit interaction for both data storage and neuromorphic computing applications.
Year
DOI
Venue
2015
10.1109/ASPDAC.2015.7059070
ASP-DAC
Keywords
Field
DocType
emerging memory, resistive switching memory, SPICE model
Spice,Computer data storage,Computer science,Design tool,Systems design,Electrical measurements,Neuromorphic engineering,Electronic engineering,Calibration,Resistive random-access memory
Conference
ISSN
Citations 
PageRank 
2153-6961
3
0.48
References 
Authors
0
8
Name
Order
Citations
PageRank
J. F. Kang171.54
Haitong Li2264.43
Huang, P.3315.61
Z. Chen430.48
Gao B54413.39
X. Y. Liu630.48
Zuhua Jiang721621.51
H.-S. Philip Wong8645106.40