Toward Efficient System-on-Module for Design-Space Exploration of Analog Spiking Neural Networks

El-Masry M, Werner T, Zjajo A, Weigel R (2024)

Publication Type: Journal article

Publication year: 2024

Journal

IEEE Transactions on Circuits and Systems I-Regular Papers Institute of Electrical and Electronics Engineers (IEEE)

Pages Range: 1-0

DOI: 10.1109/TCSI.2024.3406522

Abstract

In this paper, we present an integrated system-on-module for design-space exploration of neurosynaptic behavior in non-volatile memory enhanced spiking neural networks. The system operates in locally-analog, globally-digital modus, facilitating the exploration and validation of both, individual computational components, and the characteristic spike-based features of neurosynaptic arrays. The key advantage of the system lies in its reconfigurable, adaptable, and interchangeable components, which enable precise and reproducible firing patterns. By leveraging these capabilities, various aspects of neurosynaptic behavior can be examined and manipulated. To enhance the weight retention mechanism, the platform incorporates embedded resistive-RAM, ensuring the preservation of synaptic weights. This integration further supports the accurate representation and processing of synaptic information. Experimental results in 28 nm CMOS technology demonstrate the feasibility and effectiveness of the proposed methodology in characterizing spiking neural network components.

Authors with CRIS profile

Robert Weigel Lehrstuhl für Technische Elektronik (LTE)

Additional Organisation(s)

FAU Profilzentrum Licht.Materie.Quantentechnologien (FAU LMQ)

Involved external institutions

Infineon Technologies AG DE Germany (DE) Ferroelectric Memory GmbH DE Germany (DE) Innatera Nanosystems BV NL Netherlands (NL)

How to cite

APA:

El-Masry, M., Werner, T., Zjajo, A., & Weigel, R. (2024). Toward Efficient System-on-Module for Design-Space Exploration of Analog Spiking Neural Networks. IEEE Transactions on Circuits and Systems I-Regular Papers, 1-0. https://doi.org/10.1109/TCSI.2024.3406522

MLA:

El-Masry, Moamen, et al. "Toward Efficient System-on-Module for Design-Space Exploration of Analog Spiking Neural Networks." IEEE Transactions on Circuits and Systems I-Regular Papers (2024): 1-0.

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