The DOI matches its Crossref record; 52 of the 52 references it cites were found in a registry or an index.
Logic Design Within Memristive Memories Using Memristor-Aided loGIC (MAGIC)
Abstract
Realizing logic operations within passive crossbar memory arrays is a promising approach to enable novel computer architectures, different from conventional von Neumann architecture. Attractive candidates to enable such architectures are memristors, nonvolatile memory elements commonly used within a crossbar, that can also perform logic operations. In such novel architectures, data are stored and processed within the same entity, which we term as memristivememory processing unit(MPU). In this paper, Memristor-Aided loGIC (MAGIC) family is discussed with various design considerations and novel techniques to execute logic within an MPU. We present a novel resistive memory—thetranspose memory, which adds additional functionality to the memristive memory, and compare it with a conventional memristive memory. A case study of an adder is presented to demonstrate the design issues discussed in this paper. We compare the proposed design techniques with the memristive IMPLY logic in terms of speed, area, and energy. Our evaluation shows that the proposed MAGIC design is 2.4$\times$faster and consumes 66.3% less energy as compared with the IMPLY-based computing for N-bit addition within memristive crossbar memory. Additionally, we compare the proposed design with IMPLY logic family on ISCAS-85 benchmarks, which shows significant improvements in speed (2$\times$) and energy (10$\times$), with similar area.
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Cites
Memristor—The Missing Circuit Element
Chua, L. (1971) · IEEE Transactions on Circuit Theory · doi:10.1109/tct.1971.1083337 · Cited by 10,268 · cited 1×
“In [1], Chua proposed a fourth fundamental passive circuit element, apart from resistor, inductor, and capacitor.”
BackgroundNanoscale Memristor Device as Synapse in Neuromorphic Systems
Jo, S. H., Chang, T., Ebong, I., Bhadviya, B. B., Mazumder, P., & Lu, W. (2010) · Nano Letters · doi:10.1021/nl904092h · Cited by 4,174
Memristive devices for computing
Yang, J. J., Strukov, D. B., & Stewart, D. R. (2013) · Nature Nanotechnology · doi:10.1038/nnano.2012.240 · Cited by 3,885
Memristive 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×
“For current-controlled memristors [2], [37], the cumulative current may be higher than the threshold current, resulting in increased resistance of the output memristor, even when the logical state of the memristor is unchanged.”
Background1.1 Computing's energy problem (and what we can do about it)
Horowitz, M. (2014) · 2014 IEEE International Solid-State Circuits Conference Digest of Technical Papers (ISSCC) · doi:10.1109/isscc.2014.6757323 · Cited by 2,069
‘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
Neuromorphic Silicon Neuron Circuits
Indiveri, G., Linares-Barranco, B., Hamilton, T. J., Schaik, A. V., Etienne-Cummings, R., Delbruck, T., Liu, S.-C., Dudek, P., Häfliger, P., Renaud, S., et al. (2011) · Frontiers in Neuroscience · doi:10.3389/fnins.2011.00073 · Cited by 1,821
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
Cited by
Memory devices and applications for in-memory computing
Sebastian, A., Le Gallo, M., Khaddam-Aljameh, R., & Eleftheriou, E. (2020) · Nature Nanotechnology · doi:10.1038/s41565-020-0655-z · Cited by 2,289
Computing in Memory With Spin-Transfer Torque Magnetic RAM
Jain, S., Ranjan, A., Roy, K., & Raghunathan, A. (2018) · IEEE Transactions on Very Large Scale Integration (VLSI) Systems · doi:10.1109/tvlsi.2017.2776954 · Cited by 355
Neuromemristive 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
Computing in memory with FeFETs
Reis, D., Niemier, M., & Hu, X. S. (2018) · Proceedings of the International Symposium on Low Power Electronics and Design · doi:10.1145/3218603.3218640 · Cited by 102
Metadata
- Authors
- Talati, N., Gupta, S., Mane, P., & Kvatinsky, S.
- Venue
- IEEE Transactions on Nanotechnology
- Published
- 2016-07
- Volume
- 15
- Issue
- 4
- Pages
- 635-650
- ISSN
- 1536-125X (ISSN-L)
- 1941-0085
- OpenAlex
- W2407339173
- Cited by
- 339
- References
- 52
- FWCI
- 17.38
- Type
- journal article
- Language
- en
- Open access
- closed
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