Nonvolatile memristor memory: device characteristics and design implications
Proceedings of the 2009 International Conference on Computer-Aided Design
Proceedings of the 2010 IEEE/ACM International Symposium on Nanoscale Architectures
Impact of process variations on emerging memristor
Proceedings of the 47th Design Automation Conference
Practical approach to programmable analog circuits with memristors
IEEE Transactions on Circuits and Systems Part I: Regular Papers
Compact modeling and corner analysis of spintronic memristor
NANOARCH '09 Proceedings of the 2009 IEEE/ACM International Symposium on Nanoscale Architectures
Geometry variations analysis of TiO2 thin-film and spintronic memristors
Proceedings of the 16th Asia and South Pacific Design Automation Conference
A Memristor SPICE Implementation and a New Approach for Magnetic Flux-Controlled Memristor Modeling
IEEE Transactions on Nanotechnology
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The emerging memristor devices have recently received increased attention since HP Lab reported the first TiO2-based memristive structure. As it is at nano-scale geometry size, the uniformity of memristor device is difficult to control due to the process variations in the fabrication process. The incurred design concerns in a memristor-based computing system, e. g, neuromorphic computing, can be very severe because the analog states of memristors are heavily utilized. Therefore, the understanding and quantitative characterization of the impact of process variations on the electrical properties of memristors become crucial for the corresponding VLSI designs. In this work, we examined the theoretical model of TiO2 thin-film memristors and studied the relationships between the electrical parameters and the process variations of the devices. A statistical model based on a process-variation aware memristor device structure is extracted accordingly. Simulations show that our proposed model is 3 ~ 4 magnitude faster than the existing Monte-Carlo simulation method, with only ~ 2% accuracy degradation. A variable gain amplifier (VGA) is used as the case study to demonstrate the applications of our model in memristor-based circuit designs.