You're currently viewing an old version of this dataset. To see the current version, click here.

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.

Data and Resources

This dataset has no data

Cite this as

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

Private DOI This DOI is not yet resolvable.
It is available for use in manuscripts, and will be published when the Dataset is made public.

Additional Info

Field	Value
Created	December 2, 2024
Last update	December 2, 2024
Author	Gao Yuechao
More Authors	Liu Nianhong Zhang Sheng