OISMA: On-the-Fly In-Memory Stochastic Multiplication Architecture for Approximate Matrix Multiplication

Artificial intelligence (AI) models are currently driven by a significant upscaling of their complexity, with massive matrix-multiplication workloads representing the major computational bottleneck. In-memory computing (IMC) architectures are proposed to avoid the von Neumann bottleneck. However, bo...

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Detalhes bibliográficos

Principais autores:	Shady Agwa, Yihan Pan, Georgios Papandroulidakis, Themis Prodromakis
Formato:	Artigo
Idioma:	Inglês
Publicado em:	IEEE 2026-01-01
coleção:	IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
Assuntos:	Artificial intelligence (AI) in-memory computing (IMC) resistive random-access memory (RRAM) stochastic computing (SC) unconventional computing
Acesso em linha:	https://ieeexplore.ieee.org/document/11473289/
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