Supernetwork-based efficient mapping of deep learning applications to mixed-precision hardware using model adaptation

Abstract The rapid proliferation of Artificial Intelligence applications necessitates scalable solutions that perform efficiently under real-world constraints. Heterogeneous accelerators combining specialized analog and digital units offer localized, energy-efficient neural network computations. How...

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Bibliografische Detailangaben

Hauptverfasser:	Hadjer Benmeziane, Corey Lammie, Irem Boybat, Malte Rasch, Manuel Le Gallo, Athanasios Vasilopoulos, Hsinyu Tsai, Geoffrey W. Burr, Vijay Narayanan, Kaoutar El Maghraoui, Abu Sebastian
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	Nature Portfolio 2026-03-01
Schriftenreihe:	Nature Communications
Online-Zugang:	https://doi.org/10.1038/s41467-026-71071-1
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