Combined HW/SW drift and variability mitigation for PCM-based analog in-memory computing for neural network applications
A Antolini, C Paolino, F Zavalloni, A Lico… - IEEE Journal on …, 2023 - ieeexplore.ieee.org
Matrix-Vector Multiplications (MVMs) represent a heavy workload for both training and
inference in Deep Neural Networks (DNNs) applications. Analog In-memory Computing …
inference in Deep Neural Networks (DNNs) applications. Analog In-memory Computing …
PCM-based in-memory computing: architectures, circuits and applications
A Antolini - 2023 - amsdottorato.unibo.it
Analog In-memory Computing (AIMC) has been proposed in the context of Beyond Von
Neumann architectures as a valid strategy to reduce internal data transfers energy …
Neumann architectures as a valid strategy to reduce internal data transfers energy …