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SMAUG: End-to-End Full-Stack Simulation Infrastructure for Deep Learning Workloads


Dec 11, 2019
Sam Likun Xi, Yuan Yao, Kshitij Bhardwaj, Paul Whatmough, Gu-Yeon Wei, David Brooks

* 14 pages, 20 figures 

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A binary-activation, multi-level weight RNN and training algorithm for processing-in-memory inference with eNVM


Dec 03, 2019
Siming Ma, David Brooks, Gu-Yeon Wei


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MLPerf Training Benchmark


Oct 30, 2019
Peter Mattson, Christine Cheng, Cody Coleman, Greg Diamos, Paulius Micikevicius, David Patterson, Hanlin Tang, Gu-Yeon Wei, Peter Bailis, Victor Bittorf, David Brooks, Dehao Chen, Debojyoti Dutta, Udit Gupta, Kim Hazelwood, Andrew Hock, Xinyuan Huang, Bill Jia, Daniel Kang, David Kanter, Naveen Kumar, Jeffery Liao, Guokai Ma, Deepak Narayanan, Tayo Oguntebi, Gennady Pekhimenko, Lillian Pentecost, Vijay Janapa Reddi, Taylor Robie, Tom St. John, Carole-Jean Wu, Lingjie Xu, Cliff Young, Matei Zaharia


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AdaptivFloat: A Floating-point based Data Type for Resilient Deep Learning Inference


Oct 15, 2019
Thierry Tambe, En-Yu Yang, Zishen Wan, Yuntian Deng, Vijay Janapa Reddi, Alexander Rush, David Brooks, Gu-Yeon Wei

* 10 pages 

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Benchmarking TPU, GPU, and CPU Platforms for Deep Learning


Aug 06, 2019
Yu Emma Wang, Gu-Yeon Wei, David Brooks


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Learning Low-Rank Approximation for CNNs


May 24, 2019
Dongsoo Lee, Se Jung Kwon, Byeongwook Kim, Gu-Yeon Wei


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