Hardware-Oriented Acceleration of Deep Convolutional Neural Networks

To address memory and computation resource limitations for hardware-oriented acceleration of deep convolutional neural networks (CNNs), we present a compu-tation flow, stacked filters stationary flow (SFS), and a corresponding data encoding format, relative indexed compressed sparse filter format (CSF), to make the best of data sparsity, and simplify data handling at execution time.

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Gao Yuechao, Liu Nianhong, Zhang Sheng (2024). Dataset: Hardware-Oriented Acceleration of Deep Convolutional Neural Networks. https://doi.org/10.57702/haroqlsp

DOI retrieved: December 2, 2024

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Created December 2, 2024
Last update December 2, 2024
Author Gao Yuechao
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Liu Nianhong
Zhang Sheng