Quantization and sparsity-aware processing for energy-efficient NVM-based convolutional neural networks

Quantization and sparsity-aware processing for energy-efficient NVM-based convolutional neural networks

Nonvolatile memory (NVM)-based convolutional neural networks (NvCNNs) have received widespread attention as a promising solution for hardware edge intelligence. However, there still exist many challenges in the resource-constrained conditions, such as the limitations of the hardware precision and co...

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Bibliographic Details
Main Authors: Han Bao, Yifan Qin, Jia Chen, Ling Yang, Jiancong Li, Houji Zhou, Yi Li, Xiangshui Miao
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-08-01
Series:Frontiers in Electronics
Subjects:
NVM
convolutional neural network
in-memory computing
quantization
edge intelligence
sparsity
Online Access:https://www.frontiersin.org/articles/10.3389/felec.2022.954661/full

Internet

https://www.frontiersin.org/articles/10.3389/felec.2022.954661/full

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