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Analyzing and Mitigating Data Stalls in DNN Training

Jul 14, 2020
Jayashree Mohan, Amar Phanishayee, Ashish Raniwala, Vijay Chidambaram


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Efficient Algorithms for Device Placement of DNN Graph Operators

Jun 29, 2020
Jakub Tarnawski, Amar Phanishayee, Nikhil R. Devanur, Divya Mahajan, Fanny Nina Paravecino


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Memory-Efficient Pipeline-Parallel DNN Training

Jun 16, 2020
Deepak Narayanan, Amar Phanishayee, Kaiyu Shi, Xie Chen, Matei Zaharia


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Daydream: Accurately Estimating the Efficacy of Optimizations for DNN Training

Jun 05, 2020
Hongyu Zhu, Amar Phanishayee, Gennady Pekhimenko


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Blink: Fast and Generic Collectives for Distributed ML

Oct 11, 2019
Guanhua Wang, Shivaram Venkataraman, Amar Phanishayee, Jorgen Thelin, Nikhil Devanur, Ion Stoica


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The Non-IID Data Quagmire of Decentralized Machine Learning

Oct 01, 2019
Kevin Hsieh, Amar Phanishayee, Onur Mutlu, Phillip B. Gibbons


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Parameter Hub: a Rack-Scale Parameter Server for Distributed Deep Neural Network Training

May 21, 2018
Liang Luo, Jacob Nelson, Luis Ceze, Amar Phanishayee, Arvind Krishnamurthy


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TBD: Benchmarking and Analyzing Deep Neural Network Training

Apr 14, 2018
Hongyu Zhu, Mohamed Akrout, Bojian Zheng, Andrew Pelegris, Amar Phanishayee, Bianca Schroeder, Gennady Pekhimenko


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