The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.
Memristor-Based Material Implication (IMPLY) Logic: Design Principles and Methodologies
Abstract
Memristors are novel devices, useful as memory at all hierarchies. These devices can also behave as logic circuits. In this paper, the IMPLY logic gate, a memristor-based logic circuit, is described. In this memristive logic family, each memristor is used as an input, output, computational logic element, and latch in different stages of the computing process. The logical state is determined by the resistance of the memristor. This logic family can be integrated within a memristor-based crossbar, commonly used for memory. In this paper, a methodology for designing this logic family is proposed. The design methodology is based on a general design flow, suitable for all deterministic memristive logic families, and includes some additional design constraints to support the IMPLY logic family. An IMPLY 8-bit full adder based on this design methodology is presented as a case study.
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Cites
Strukov, D. B., Snider, G. S., Stewart, D. R., & Williams, R. S. (2008) · Nature · doi:10.1038/nature06932 · Cited by 11,828
Memristor—The Missing Circuit Element
Chua, L. (1971) · IEEE Transactions on Circuit Theory · doi:10.1109/tct.1971.1083337 · Cited by 10,268 · cited 5×
“MEMRISTORS [1] and memristive devices [2] are novel structures, useful in many applications.”
BackgroundMethodInfluentialMemristive switching mechanism for metal/oxide/metal nanodevices
Yang, J. J., Pickett, M. D., Li, X., Ohlberg, D. A. A., Stewart, D. R., & Williams, R. S. (2008) · Nature Nanotechnology · doi:10.1038/nnano.2008.160 · Cited by 2,987
Memristive devices and systems
Chua, L. O., & Kang, S. M. (1976) · Proceedings of the IEEE · doi:10.1109/proc.1976.10092 · Cited by 2,604 · cited 2×
“The theory of memristors was extended to memristive devices in 1976 [2].”
Background‘Memristive’ switches enable ‘stateful’ logic operations via material implication
Borghetti, J., Snider, G. S., Kuekes, P. J., Yang, J. J., Stewart, D. R., & Williams, R. S. (2010) · Nature · doi:10.1038/nature08940 · Cited by 1,929
Resistance switching memories are memristors
Chua, L. (2011) · Applied Physics A · doi:10.1007/s00339-011-6264-9 · Cited by 1,434
Complementary resistive switches for passive nanocrossbar memories
Linn, E., Rosezin, R., Kügeler, C., & Waser, R. (2010) · Nature Materials · doi:10.1038/nmat2748 · Cited by 1,274
SPICE Model of Memristor with Nonlinear Dopant Drift
Biolek, Z., Biolek, D., & Biolková, V. (2009) · Brno University of Technology Digital Library (Brno University of Technology) · Cited by 1,099
TEAM: ThrEshold Adaptive Memristor Model
Kvatinsky, S., Friedman, E. G., Kolodny, A., & Weiser, U. C. (2013) · IEEE Transactions on Circuits and Systems I: Regular Papers · doi:10.1109/tcsi.2012.2215714 · Cited by 843
Self-citationSwitching dynamics in titanium dioxide memristive devices
Pickett, M. D., Strukov, D. B., Borghetti, J. L., Yang, J. J., Snider, G. S., Stewart, D. R., & Williams, R. S. (2009) · Journal of Applied Physics · doi:10.1063/1.3236506 · Cited by 764
Cited by
Kvatinsky, S., Belousov, D., Liman, S., Satat, G., Wald, N., Friedman, E. G., Kolodny, A., & Weiser, U. C. (2014) · IEEE Transactions on Circuits and Systems II: Express Briefs · doi:10.1109/tcsii.2014.2357292 · Cited by 835
Self-citationLogic Design Within Memristive Memories Using Memristor-Aided loGIC (MAGIC)
Talati, N., Gupta, S., Mane, P., & Kvatinsky, S. (2016) · IEEE Transactions on Nanotechnology · doi:10.1109/tnano.2016.2570248 · Cited by 339
Self-citationNeuromemristive Circuits for Edge Computing: A Review
Krestinskaya, O., James, A. P., & Chua, L. O. (2020) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2019.2899262 · Cited by 319
Memristor-Based Multilayer Neural Networks With Online Gradient Descent Training
Soudry, D., Di Castro, D., Gal, A., Kolodny, A., & Kvatinsky, S. (2015) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2014.2383395 · Cited by 271
Self-citationMemristive Crossbar Arrays for Storage and Computing Applications
Li, H., Wang, S., Zhang, X., Wang, W., Yang, R., Sun, Z., Feng, W., Lin, P., Wang, Z., Sun, L., et al. (2021) · Advanced Intelligent Systems · doi:10.1002/aisy.202100017 · Cited by 205
Metadata
- Authors
- Kvatinsky, S., Satat, G., Wald, N., Friedman, E. G., Kolodny, A., & Weiser, U. C.
- Venue
- IEEE Transactions on Very Large Scale Integration (VLSI) Systems
- Published
- 2014-10
- Volume
- 22
- Issue
- 10
- Pages
- 2054-2066
- ISSN
- 1063-8210 (ISSN-L)
- 1557-9999
- OpenAlex
- W2066280488
- Cited by
- 677
- References
- 38
- FWCI
- 16.78
- Type
- journal article
- Language
- en
- Open access
- closed
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- Kvatinsky, S., Satat, G., Wald, N., Friedman, E. G., Kolodny, A., & Weiser, U. C. (2014). Memristor-Based Material Implication (IMPLY) Logic: Design Principles and Methodologies. IEEE Transactions on Very Large Scale Integration (VLSI) Systems. https://doi.org/10.1109/tvlsi.2013.2282132
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