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Picture for Gyeong-In Yu

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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A Tensor Compiler for Unified Machine Learning Prediction Serving


Oct 19, 2020
Supun Nakandala, Karla Saur, Gyeong-In Yu, Konstantinos Karanasos, Carlo Curino, Markus Weimer, Matteo Interlandi


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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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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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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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