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Gradient Disaggregation: Breaking Privacy in Federated Learning by Reconstructing the User Participant Matrix

Jun 10, 2021
Maximilian Lam, Gu-Yeon Wei, David Brooks, Vijay Janapa Reddi, Michael Mitzenmacher

* ICML 2021 

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MAVFI: An End-to-End Fault Analysis Framework with Anomaly Detection and Recovery for Micro Aerial Vehicles

May 27, 2021
Yu-Shun Hsiao, Zishen Wan, Tianyu Jia, Radhika Ghosal, Arijit Raychowdhury, David Brooks, Gu-Yeon Wei, Vijay Janapa Reddi

* 14 pages, 16 figures 

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RecPipe: Co-designing Models and Hardware to Jointly Optimize Recommendation Quality and Performance

May 22, 2021
Udit Gupta, Samuel Hsia, Jeff Zhang, Mark Wilkening, Javin Pombra, Hsien-Hsin S. Lee, Gu-Yeon Wei, Carole-Jean Wu, David Brooks

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Machine Learning-Based Automated Design Space Exploration for Autonomous Aerial Robots

Feb 05, 2021
Srivatsan Krishnan, Zishen Wan, Kshitij Bharadwaj, Paul Whatmough, Aleksandra Faust, Sabrina Neuman, Gu-Yeon Wei, David Brooks, Vijay Janapa Reddi

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RecSSD: Near Data Processing for Solid State Drive Based Recommendation Inference

Jan 29, 2021
Mark Wilkening, Udit Gupta, Samuel Hsia, Caroline Trippel, Carole-Jean Wu, David Brooks, Gu-Yeon Wei

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EdgeBERT: Optimizing On-Chip Inference for Multi-Task NLP

Dec 01, 2020
Thierry Tambe, Coleman Hooper, Lillian Pentecost, En-Yu Yang, Marco Donato, Victor Sanh, Alexander M. Rush, David Brooks, Gu-Yeon Wei

* 11 pages plus references 

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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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Exploiting Parallelism Opportunities with Deep Learning Frameworks

Aug 13, 2019
Yu Emma Wang, Carole-Jean Wu, Xiaodong Wang, Kim Hazelwood, David Brooks

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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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The Architectural Implications of Facebook's DNN-based Personalized Recommendation

Jun 18, 2019
Udit Gupta, Xiaodong Wang, Maxim Naumov, Carole-Jean Wu, Brandon Reagen, David Brooks, Bradford Cottel, Kim Hazelwood, Bill Jia, Hsien-Hsin S. Lee, Andrey Malevich, Dheevatsa Mudigere, Mikhail Smelyanskiy, Liang Xiong, Xuan Zhang

* 11 pages 

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Cloud No Longer a Silver Bullet, Edge to the Rescue

Feb 15, 2018
Yuhao Zhu, Gu-Yeon Wei, David Brooks

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Weightless: Lossy Weight Encoding For Deep Neural Network Compression

Nov 13, 2017
Brandon Reagen, Udit Gupta, Robert Adolf, Michael M. Mitzenmacher, Alexander M. Rush, Gu-Yeon Wei, David Brooks

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Fathom: Reference Workloads for Modern Deep Learning Methods

Aug 23, 2016
Robert Adolf, Saketh Rama, Brandon Reagen, Gu-Yeon Wei, David Brooks

* Proceedings of the IEEE International Symposium on Workload Characterization, 2016 

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