Non-volatile Memory Technologies for Neuromorphic Computing
A special issue of Micromachines (ISSN 2072-666X). This special issue belongs to the section "E：Engineering and Technology".
Deadline for manuscript submissions: closed (20 September 2022) | Viewed by 860
Special Issue Editors
Interests: digital VLSI; semiconductor devices; non-volatile memories; neuromorphic computing
Interests: nanoelectronics; emerging memory devices; neuromorphic hardware; cryogenic electronics; beyond cmos device
Special Issues, Collections and Topics in MDPI journals
Interests: emerging technologies; circuit design; system architecture; memory design; non-boolean computing; low power systems; security; machine learning; genomics
Special Issue Information
Dear Colleagues,
The emergence of new data-intensive applications has led to a pressing need for enabling cognitive capabilities in the electronic systems. Towards that end, neuromorphic computing has shown an immense potential, wherein the artificial neurons and synapses and their complex network lead to a massively parallel processing of data with a tight compute-memory coupling. To realize such a fabric, technologies beyond standard CMOS need to be explored that are amenable to the distinct functionality requirements of neuromorphic architectures. In particular, non-volatile devices assume a prime importance for not only enabling low power inference but also supporting efficient and adaptive training mechanisms. This Special Issue aims to bring together the advancements in non-volatile memory technologies targeted towards neuromorphic computing. Contributions are sought in diverse areas spanning experimental studies of such technologies, device-circuit co-design of synaptic sub-systems, explorations of novel neural network architectures supported by the emerging non-volatile devices and the development of new learning algorithms enabled by the unique properties of the non-volatile memory technologies. This issue invites novel contributions, review papers and perspective articles on these topics.
Prof. Dr. Sumeet Kumar Gupta
Prof. Dr. Ahmedullah Aziz
Prof. Dr. Sumitha George
Guest Editors
Manuscript Submission Information
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Keywords
- cross-point architectures
- computing in memory
- deep neural networks
- ferroelectrics
- mrams
- neurons
- phase change memories
- resistive rams
- spiking neural networks
- spintronics
- synapses
