Abstract: Linear INT8 quantization is presented to construct an end to end integer-only dataflow for efficient inference of modern CNNs.

Aiming at constructing efficient CNN accelerator deployed on FPGAs / ASICs, an INT8 quantization is proposed in this paper to realize end-to-end integer-only ...

For example, in [11] , authors propose an end-to-end 8-bit integer model without internal conversions to floating-point data types. As a result, such a model ...

Feb 8, 2023 · While these approaches allow neural network models to execute more efficiently once the input data are in place, for computer vision tasks, ...

Experiments using the. CNN configurations of AlexNet show that the proposed RS dataflow is more energy efficient than existing dataflows in both convolutional ( ...

CNN Background. • A convolutional neural network (CNN) is constructed by stacking multiple computation layers as a directed acyclic graph.

Mar 19, 2023 · As an application of this framework, the article presents a simple pruning strategy for considering the dataflow design space exploration and “ ...

In this paper, we propose a dimensionality reduction method applied to tensor-structured data as a hidden layer (we call it TensorProjection Layer) in a ...

Convolutional neural networks (CNN) is a specialized case of artificial neural networks(ANN) and finds its application in computer vision and parallel ...

A collection of research papers on efficient training of DNNs. If you find some ignored papers, please open issues or pull requests. Contents. Algorithm.