Compact Modeling and Mitigation of Parasitics in Crosspoint Accelerators of Neural Networks

In-memory computing (IMC) can accelerate data-intensive tasks, such as matrix-vector multiplication (MVM) or artificial neural networks (ANNs) inference, by means of the crosspoint memory array, allowing to reduce time and energy consumption. IMC accuracy, however, is affected by nonidealities, such...

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Vydané v:	IEEE transactions on electron devices Ročník 71; číslo 3; s. 1 - 7
Hlavní autori:	Lepri, N., Glukhov, A., Mannocci, P., Porzani, M., Ielmini, D.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.03.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Accuracy Arrays Artificial neural networks Deep learning emerging memory technologies Energy consumption hardware accelerator in-memory computing (IMC) Logic gates Mathematical analysis Matrix algebra Microprocessors Programming Resistance resistive switching memory (RRAM) Transistors Voltage Wires
ISSN:	0018-9383, 1557-9646
On-line prístup:	Získať plný text
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