Get our free extension to see links to code for papers anywhere online!

Chrome logo  Add to Chrome

Firefox logo Add to Firefox

Terra: Imperative-Symbolic Co-Execution of Imperative Deep Learning Programs


Jan 23, 2022
Taebum Kim, Eunji Jeong, Geon-Woo Kim, Yunmo Koo, Sehoon Kim, Gyeong-In Yu, Byung-Gon Chun

* 35th Conference on Neural Information Processing Systems (NeurIPS 2021) 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

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 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

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


   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

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


   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

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 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

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


   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

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 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

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 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

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 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Mantis: Predicting System Performance through Program Analysis and Modeling


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


   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email