Automatic generation of high-performance quantized machine learning kernels-Reference-Cited by-同舟云学术

Automatic generation of high-performance quantized machine learning kernels

Published:2020-02-21 Issue: Volume: Page:
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Container-title:Proceedings of the 18th ACM/IEEE International Symposium on Code Generation and Optimization
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Author:

Cowan Meghan¹,Moreau Thierry¹,Chen Tianqi¹,Bornholt James²,Ceze Luis¹

Affiliation:

1. University of Washington, USA

2. University of Texas at Austin, USA

Funder

National Science Foundation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3368826.3377912

Reference45 articles.

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2. James Bornholt Emina Torlak Dan Grossman and Luis Ceze. 2016. Optimizing synthesis with metasketches. In POPL. James Bornholt Emina Torlak Dan Grossman and Luis Ceze. 2016. Optimizing synthesis with metasketches. In POPL.

3. Zhaowei Cai Xiaodong He Jian Sun and Nuno Vasconcelos. 2017. Deep learning with low precision by half-wave gaussian quantization. In CVPR. Zhaowei Cai Xiaodong He Jian Sun and Nuno Vasconcelos. 2017. Deep learning with low precision by half-wave gaussian quantization. In CVPR.

4. Tianqi Chen Lianmin Zheng Eddie Yan Ziheng Jiang Thierry Moreau Luis Ceze Carlos Guestrin and Arvind Krishnamurthy. 2018. Learning to optimize tensor programs. In NeurIPS. Tianqi Chen Lianmin Zheng Eddie Yan Ziheng Jiang Thierry Moreau Luis Ceze Carlos Guestrin and Arvind Krishnamurthy. 2018. Learning to optimize tensor programs. In NeurIPS.

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