Hybrid Magneto-electric FET-CMOS Integrated Memory Design for Instant-on Computing

Deniz Najafi, Sepehr Tabrizchi, Ranyang Zhou, Mohammadreza Amel Solouki, Andrew Marshal, Arman Roohi, Shaahin Angizi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The surge in the number of normally-off power-constraint Internet of Things (IoT) devices in recent years has amplified the demand for high-performance and energy-efficient in-memory computing architectures built on top of various non-volatile memories. Magneto-Electric Field Effect Transistors (MEFETs) have presented compelling design features suitable for logic and memory integration as an emerging post-CMOS FET. These include high-speed switching, minimal power usage, and non-volatility. This work introduces a new in-memory computing architecture designed for edge applications, leveraging emerging MEFETs. The proposed architecture enables the execution of both Boolean logic operations and Binary Content Addressable Memory (BCAM) operations within a single cycle. Furthermore, the energy consumption during the write operation of the proposed cell is optimized by introducing a new write circuitry. The outcomes of our device-to-architecture evaluation reveal approximately 43.5% and 96.9% reduction in read and write energy consumption, respectively, compared to the counterpart non-volatile memories. At the application level, the proposed architecture is applied to implement Binary Neural Networks (BNNs) based on AlexNet and VGG16. Our results showcase a decrease of approximately 54% in the overall energy consumption when implementing these networks using the proposed design compared to non-volatile in-memory computing designs.

Original languageEnglish (US)
Title of host publicationGLSVLSI 2024 - Proceedings of the Great Lakes Symposium on VLSI 2024
PublisherAssociation for Computing Machinery
Pages770-775
Number of pages6
ISBN (Electronic)9798400706059
DOIs
StatePublished - Jun 12 2024
Event34th Great Lakes Symposium on VLSI 2024, GLSVLSI 2024 - Clearwater, United States
Duration: Jun 12 2024Jun 14 2024

Publication series

NameProceedings of the ACM Great Lakes Symposium on VLSI, GLSVLSI

Conference

Conference34th Great Lakes Symposium on VLSI 2024, GLSVLSI 2024
Country/TerritoryUnited States
CityClearwater
Period6/12/246/14/24

All Science Journal Classification (ASJC) codes

  • General Engineering

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