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High precision tuning of state for memristive devices by adaptable variation-tolerant algorithm
Open accessAbstract
Using memristive properties common for titanium dioxide thin film devices, we designed a simple write algorithm to tune device conductance at a specific bias point to 1% relative accuracy (which is roughly equivalent to seven-bit precision) within its dynamic range even in the presence of large variations in switching behavior. The high precision state is nonvolatile and the results are likely to be sustained for nanoscale memristive devices because of the inherent filamentary nature of the resistive switching. The proposed functionality of memristive devices is especially attractive for analog computing with low precision data. As one representative example we demonstrate hybrid circuitry consisting of an integrated circuit summing amplifier and two memristive devices to perform the analog multiply-and-add (dot-product) computation, which is a typical bottleneck operation in information processing.
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“To program an RRAM cell to its target conductance, we use an incremental-pulse write–verify technique42.”
From A compute-in-memory chip based on resistive random-access memory (2022) · cites this paper as [42]
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Cited by
Sorted by citations
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
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“Such multilevel behaviour has been exploited by a number of researchers 62–64 , showing repeatable state control from 5 different conductance levels (over 2 bits) to over 64 levels (6 bits) for a single memristor.”
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Metadata
- Authors
- Alibart, F., Gao, L., Hoskins, B. D., & Strukov, D. B.
- Affiliations
- University of California, Santa Barbara (US)
- Venue
- Nanotechnology
- Publisher
- IOP Publishing
- Published
- 2012-01-20
- Volume
- 23
- Issue
- 7
- Pages
- 075201
- ISSN
- 0957-4484 (ISSN-L)
- 1361-6528
- OpenAlex
- W2091777687
- Cited by
- 557
- References
- 35
- Citations by year
- 2026: 9 · 2025: 26 · 2024: 21 · 2023: 37 · 2022: 37 · 2021: 45 · 2020: 56 · 2019: 73 · 2018: 58 · 2017: 43 · 2016: 47 · 2015: 39 · 2014: 27 · 2013: 22 · 2012: 16
- FWCI
- 21.27
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Nanotechnology (publishedVersion)
- PubMed (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- National Science Foundation (1028336, 1121053)
- Division of Materials Research (DMR 1121053, 1121053)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Memory and Neural Computing
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Ferroelectric and Negative Capacitance Devices
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advancements in Semiconductor Devices and Circuit Design
- Keywords
- memristors, TiO2 thin films, resistive switching, conductance tuning, variation tolerance, filamentary switching, non-volatile memory, analog computing, dot product computation, summing amplifier
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