Ansor: Generating High-Performance Tensor Programs for Deep Learning (English)
- New search for: Zheng, Lianmin
- New search for: Jia, Chengfan
- New search for: Sun, Minmin
- New search for: Wu, Zhao
- New search for: Yu, Cody Hao
- New search for: Ali, Ameer Haj
- New search for: Wang, Yida
- New search for: Yang, Jun
- New search for: Zhuo, Danyang
- New search for: Sen, Koushik
- New search for: Gonzalez, Joseph E.
- New search for: Stoica, Ion
- New search for: Zheng, Lianmin
- New search for: Jia, Chengfan
- New search for: Sun, Minmin
- New search for: Wu, Zhao
- New search for: Yu, Cody Hao
- New search for: Ali, Ameer Haj
- New search for: Wang, Yida
- New search for: Yang, Jun
- New search for: Zhuo, Danyang
- New search for: Sen, Koushik
- New search for: Gonzalez, Joseph E.
- New search for: Stoica, Ion
In:
14th USENIX Symposium on Operating Systems Design and Implementation (OSDI'20) ; Volume 2 of 2
; 863-880
;
2020
- Conference paper / Print
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Title:Ansor: Generating High-Performance Tensor Programs for Deep Learning
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Contributors:Zheng, Lianmin ( author ) / Jia, Chengfan ( author ) / Sun, Minmin ( author ) / Wu, Zhao ( author ) / Yu, Cody Hao ( author ) / Ali, Ameer Haj ( author ) / Wang, Yida ( author ) / Yang, Jun ( author ) / Zhuo, Danyang ( author ) / Sen, Koushik ( author )
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Conference:USENIX Symposium on Operating Systems Design and Implementation ; 14. ; 2020 ; Online
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Published in:
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Publisher:
- New search for: Curran Associates, Inc.
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Place of publication:Red Hook, NY
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Publication date:2020
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Type of media:Conference paper
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Type of material:Print
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Language:English
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Source:
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