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Greenformer: Factorization Toolkit for Efficient Deep Neural Networks

Authors :
Cahyawijaya, Samuel
Winata, Genta Indra
Lovenia, Holy
Wilie, Bryan
Dai, Wenliang
Ishii, Etsuko
Fung, Pascale
Publication Year :
2021

Abstract

While the recent advances in deep neural networks (DNN) bring remarkable success, the computational cost also increases considerably. In this paper, we introduce Greenformer, a toolkit to accelerate the computation of neural networks through matrix factorization while maintaining performance. Greenformer can be easily applied with a single line of code to any DNN model. Our experimental results show that Greenformer is effective for a wide range of scenarios. We provide the showcase of Greenformer at https://samuelcahyawijaya.github.io/greenformer-demo/.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2109.06762
Document Type :
Working Paper