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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Bibliografische Detailangaben

Hauptverfasser:	Shady Agwa, Yihan Pan, Georgios Papandroulidakis, Themis Prodromakis
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	IEEE 2026-01-01
Schriftenreihe:	IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
Schlagworte:	Artificial intelligence (AI) in-memory computing (IMC) resistive random-access memory (RRAM) stochastic computing (SC) unconventional computing
Online-Zugang:	https://ieeexplore.ieee.org/document/11473289/
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