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Hardware Acceleration for Machine Learning

Year: 2026

Type: article

Abstract: In recent years, hardware acceleration for machine learning has made significant strides, evolving from general-purpose solutions to increasingly specialized heterogeneous platforms designed to integrate artificial intelligence directly into embedded systems and edge architectures [...]

Source: Electronics

DOI: 10.3390/electronics15091857

Authors: Sergio Spanò, Gian Carlo Cardarilli, Luca Di Nunzio

Institution: University of Rome Tor Vergata

Language: English

Topic: Parallel Computing and Optimization Techniques

Subfield: Hardware and Architecture

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,896

OpenAlex ID: W7156918637

FWCI:

Cites: 5

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