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Nimble: Lightweight and Parallel GPU Task Scheduling for Deep Learning

Dec 04, 2020
Woosuk Kwon, Gyeong-In Yu, Eunji Jeong, Byung-Gon Chun

* In NeurIPS 2020 

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Accelerating Multi-Model Inference by Merging DNNs of Different Weights

Sep 28, 2020
Joo Seong Jeong, Soojeong Kim, Gyeong-In Yu, Yunseong Lee, Byung-Gon Chun

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Hippo: Taming Hyper-parameter Optimization of Deep Learning with Stage Trees

Jun 22, 2020
Ahnjae Shin, Do Yoon Kim, Joo Seong Jeong, Byung-Gon Chun

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Stage-based Hyper-parameter Optimization for Deep Learning

Nov 24, 2019
Ahnjae Shin, Dong-Jin Shin, Sungwoo Cho, Do Yoon Kim, Eunji Jeong, Gyeong-In Yu, Byung-Gon Chun

* Workshop on Systems for ML at NeurIPS 2019 

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Making Classical Machine Learning Pipelines Differentiable: A Neural Translation Approach

Jun 10, 2019
Gyeong-In Yu, Saeed Amizadeh, Artidoro Pagnoni, Byung-Gon Chun, Markus Weimer, Matteo Interlandi

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JANUS: Fast and Flexible Deep Learning via Symbolic Graph Execution of Imperative Programs

Dec 04, 2018
Eunji Jeong, Sungwoo Cho, Gyeong-In Yu, Joo Seong Jeong, DongJin Shin, Byung-Gon Chun

* NSDI 2019 
* To appear at NSDI 2019 

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PRETZEL: Opening the Black Box of Machine Learning Prediction Serving Systems

Oct 14, 2018
Yunseong Lee, Alberto Scolari, Byung-Gon Chun, Marco Domenico Santambrogio, Markus Weimer, Matteo Interlandi

* 16 pages, 14 figures, 13th USENIX Symposium on Operating Systems Design and Implementation (OSDI), 2018 

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Improving the Expressiveness of Deep Learning Frameworks with Recursion

Sep 04, 2018
Eunji Jeong, Joo Seong Jeong, Soojeong Kim, Gyeong-In Yu, Byung-Gon Chun

* EuroSys 2018: Thirteenth EuroSys Conference, April 23-26, 2018, Porto, Portugal 
* Appeared in EuroSys 2018. 13 pages, 11 figures 

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Mantis: Predicting System Performance through Program Analysis and Modeling

Sep 30, 2010
Byung-Gon Chun, Ling Huang, Sangmin Lee, Petros Maniatis, Mayur Naik

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