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Live Demonstration: Hardware/Software Co-Design to Exploit RRAM Programmability for Emerging Edge Classification Using ArC TWO

Year: 2025

Type: conference-paper

Abstract: In this demonstration, we present a hardware/software co-design methodology for Convolutional Neural Networks, where the classification section is managed through Resistive RAMs (RRAMs). To this aim, RRAM arrays are mounted onto the ArC TWO instrumentation board, which is interfaced to a laptop. A software Python front-end executes convolutional layers for feature extraction, generates stimuli for RRAMs, and controls the instrumentation board. As a proof of concept, handwritten digits classification is exhibited.

Source: IEEE International Symposium on Circuits and Systems proceedings

DOI: 10.1109/iscas56072.2025.11044243

Authors: Cristian Sestito, Georgios Papandroulidakis, Patrick Foster, Spyros Stathopoulos, Shady Agwa, Themis Prodromakis

Institution: University of Edinburgh

Language: English

Topic: Advanced Memory and Neural Computing

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: green

Funder: Engineering and Physical Sciences Research Council

OpenAlex ID: W4411727613

FWCI:

Cites: 2

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Related to: 10