Device Specifications for Neural Network Training with Analog Resistive Cross‐Point Arrays Using Tiki‐Taka Algorithms

Recently, specialized training algorithms for analog cross‐point array‐based neural network accelerators have been introduced to counteract device non‐idealities such as update asymmetry and cycle‐to‐cycle variation, achieving software‐level performance in neural network training. However, a quantit...

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Vydané v:	Advanced intelligent systems Ročník 7; číslo 5
Hlavní autori:	Byun, Jinho, Kim, Seungkun, Kim, Doyoon, Lee, Jimin, Ji, Wonjae, Kim, Seyoung
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Weinheim John Wiley & Sons, Inc 01.05.2025 Wiley
Predmet:	Accuracy Algorithms analog in‐memory computing Arrays Asymmetry deep learning accelerator device specification Energy efficiency neural network Neural networks Pattern recognition Regression analysis Specifications Tiki‐Taka algorithm
ISSN:	2640-4567, 2640-4567
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