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Cloud Collectives: Towards Cloud-aware Collectives forML Workloads with Rank Reordering


May 28, 2021
Liang Luo, Jacob Nelson, Arvind Krishnamurthy, Luis Ceze


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Accelerating SpMM Kernel with Cache-First Edge Sampling for Graph Neural Networks


Apr 23, 2021
Chien-Yu Lin, Liang Luo, Luis Ceze


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Automated Backend-Aware Post-Training Quantization


Mar 27, 2021
Ziheng Jiang, Animesh Jain, Andrew Liu, Josh Fromm, Chengqian Ma, Tianqi Chen, Luis Ceze


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Learning to Optimize Tensor Programs


Oct 27, 2018
Tianqi Chen, Lianmin Zheng, Eddie Yan, Ziheng Jiang, Thierry Moreau, Luis Ceze, Carlos Guestrin, Arvind Krishnamurthy

* NIPS 2018 

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Automating Generation of Low Precision Deep Learning Operators


Oct 25, 2018
Meghan Cowan, Thierry Moreau, Tianqi Chen, Luis Ceze

* 10 pages, 11 figures 

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TVM: An Automated End-to-End Optimizing Compiler for Deep Learning


Oct 05, 2018
Tianqi Chen, Thierry Moreau, Ziheng Jiang, Lianmin Zheng, Eddie Yan, Meghan Cowan, Haichen Shen, Leyuan Wang, Yuwei Hu, Luis Ceze, Carlos Guestrin, Arvind Krishnamurthy

* Significantly improved version, add automated optimization 

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VTA: An Open Hardware-Software Stack for Deep Learning


Jul 11, 2018
Thierry Moreau, Tianqi Chen, Ziheng Jiang, Luis Ceze, Carlos Guestrin, Arvind Krishnamurthy

* 16 pages, 2 reference pages, 16 figures 

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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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MATIC: Learning Around Errors for Efficient Low-Voltage Neural Network Accelerators


Mar 23, 2018
Sung Kim, Patrick Howe, Thierry Moreau, Armin Alaghi, Luis Ceze, Visvesh Sathe

* 6 pages, 12 figures, 3 tables. Published at Design, Automation and Test in Europe Conference and Exhibition (DATE) 2018 

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