Mixed-mode in-memory computing: towards high-performance logic processing in a memristive crossbar array

In-memory computing is a promising alternative to traditional computer designs, as it helps overcome performance limits caused by the separation of memory and processing units. However, many current approaches struggle with unreliable device behavior, which affects data accuracy and efficiency. In this work, the authors present a new computing method that combines two types of operations-those based on electrical resistance and those based on voltage-within each memory cell. This design improves reliability and avoids the need for expensive current measurements. A new software tool also helps automate the design process, supporting highly parallel operations in dense two-dimensional memory arrays. The approach balances speed and space, making it practical for advanced computing tasks. Demonstrations include a digital adder and a key part of encryption module, showing both strong performance and accuracy. This work offers a new direction for reliable and efficient in-memory computing systems with real-world applications.

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Publication Details

Journal
Communications Engineering
Published
2025-09-24
DOI
https://doi.org/10.1038/s44172-025-00461-y
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.00

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article

Mixed-mode in-memory computing: towards high-performance logic processing in a memristive crossbar array

Ziang Chen, Xianyue Zhao, Ilia Polian, Hans Krüger et al.
Communications Engineering
Advanced Memory and Neural Computing
article

Mixed-mode in-memory computing: towards high-performance logic processing in a memristive crossbar array

Ziang Chen, Xianyue Zhao, Ilia Polian, Hans Krüger, Nan Du, Christopher Bengel, Li-Wei Chen, Stephan Menzel, Massimiliano Di Ventra, Feng Liu, Kefeng Li, Uwe Hübner
article en

Abstract

In-memory computing is a promising alternative to traditional computer designs, as it helps overcome performance limits caused by the separation of memory and processing units. However, many current approaches struggle with unreliable device behavior, which affects data accuracy and efficiency. In this work, the authors present a new computing method that combines two types of operations-those based on electrical resistance and those based on voltage-within each memory cell. This design improves reliability and avoids the need for expensive current measurements. A new software tool also helps automate the design process, supporting highly parallel operations in dense two-dimensional memory arrays. The approach balances speed and space, making it practical for advanced computing tasks. Demonstrations include a digital adder and a key part of encryption module, showing both strong performance and accuracy. This work offers a new direction for reliable and efficient in-memory computing systems with real-world applications.

Communications EngineeringVol. 4(1)
University of Stuttgart (DE), Forschungszentrum Jülich (DE), Leibniz Institute of Photonic Technology (DE), University of California San Diego (US), Friedrich Schiller University Jena (DE), RWTH Aachen University (DE)
National Science Foundation, Deutsche Forschungsgemeinschaft, Bundesministerium für Bildung und Forschung, Division of Electrical, Communications and Cyber Systems
Openalex Percentile: Top 74%
Advanced Memory and Neural Computing
DOIOpen Access PDFOpenAlex
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