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HAWQV3: Dyadic Neural Network Quantization [article]

Zhewei Yao, Zhen Dong, Zhangcheng Zheng, Amir Gholami, Jiali Yu, Eric Tan, Leyuan Wang, Qijing Huang, Yida Wang, Michael W. Mahoney, Kurt Keutzer
2021 arXiv   pre-print
This hidden cost limits the latency improvement realized by quantizing Neural Networks. To address this, we present HAWQV3, a novel mixed-precision integer-only quantization framework.  ...  Current low-precision quantization algorithms often have the hidden cost of conversion back and forth from floating point to quantized integer values.  ...  Adaptive quantization for deep neural network. arXiv preprint arXiv:1712.01048, 2017b.  ... 
arXiv:2011.10680v3 fatcat:xjbfg4cpqrbc7bp2fbztj5jyea

HAWQ-V3: Dyadic Neural Network Quantization

Zhewei Yao, Zhen Dong, Zhangcheng Zheng, Amir Gholami, Jiali Yu, Eric Tan, Leyuan Wang, Qijing Huang, Yida Wang, Michael W. Mahoney, Kurt Keutzer
2021 International Conference on Machine Learning  
This hidden cost limits the latency improvement realized by quantizing Neural Networks. To address this, we present HAWQ-V3, a novel mixed-precision integer-only quantization framework.  ...  Current low-precision quantization algorithms often have the hidden cost of conversion back and forth from floating point to quantized integer values.  ...  Over the past decade, we have observed significant improvements in the accuracy of Neural Networks (NNs) for various tasks.  ... 
dblp:conf/icml/YaoDZGYTW0WMK21 fatcat:q76iqcffj5hmhhtrqqd3py7r3e

A Survey of Quantization Methods for Efficient Neural Network Inference [article]

Amir Gholami, Sehoon Kim, Zhen Dong, Zhewei Yao, Michael W. Mahoney, Kurt Keutzer
2021 arXiv   pre-print
In this article, we survey approaches to the problem of quantizing the numerical values in deep Neural Network computations, covering the advantages/disadvantages of current methods.  ...  Thus, it is not surprising that quantization has emerged recently as an important and very active sub-area of research in the efficient implementation of computations associated with Neural Networks.  ...  Dyadic quantization is another class of integer-only quantization, where all the scaling is performed with dyadic numbers, which are rational numbers with integer values in their numerator and a power  ... 
arXiv:2103.13630v3 fatcat:5274u5yy65ch7erdt3waqz4di4

Applications and Techniques for Fast Machine Learning in Science

Allison McCarn Deiana, Nhan Tran, Joshua Agar, Michaela Blott, Giuseppe Di Guglielmo, Javier Duarte, Philip Harris, Scott Hauck, Mia Liu, Mark S. Neubauer, Jennifer Ngadiuba, Seda Ogrenci-Memik (+35 others)
2022 Frontiers in Big Data  
HAWQV3: Dyadic neural network quantization. arXiv preprint arXiv:2011.10680. Yao, Z., Gholami, A., Keutzer, K., and Mahoney, M. (2019). Pyhessian: Neural networks through the lens of the hessian.  ...  A survey of quantization methods for efficient neural network inference.  ... 
doi:10.3389/fdata.2022.787421 pmid:35496379 pmcid:PMC9041419 fatcat:5w2exf7vvrfvnhln7nj5uppjga