Gyeong-In Yu

20 papers A* 5A 3Misc 1Journal 11
YearRankTypeTitle / Venue / Authors
2023 A* conf
BPipe: Memory-Balanced Pipeline Parallelism for Training Large Language Models.
ICML
Taebum Kim, Hyoungjoo Kim, Gyeong-In Yu, Byung-Gon Chun
2022 A* conf
Orca: A Distributed Serving System for Transformer-Based Generative Models.
OSDI
Gyeong-In Yu, Joo Seong Jeong, Geon-Woo Kim, Soojeong Kim, Byung-Gon Chun
2022 J jnl
Terra: Imperative-Symbolic Co-Execution of Imperative Deep Learning Programs.
CoRR
Taebum Kim, Eunji Jeong, Geon-Woo Kim, Yunmo Koo, Sehoon Kim, Gyeong-In Yu, Byung-Gon Chun
2021 A* conf
Terra: Imperative-Symbolic Co-Execution of Imperative Deep Learning Programs.
NeurIPS
Taebum Kim, Eunji Jeong, Geon-Woo Kim, Yunmo Koo, Sehoon Kim, Gyeong-In Yu, Byung-Gon Chun
2021 J jnl
WindTunnel: Towards Differentiable ML Pipelines Beyond a Single Modele.
Proc. VLDB Endow.
Gyeong-In Yu, Saeed Amizadeh, Sehoon Kim, Artidoro Pagnoni, Ce Zhang, Byung-Gon Chun, Markus Weimer, Matteo Interlandi
2020 A* conf
A Tensor Compiler for Unified Machine Learning Prediction Serving.
OSDI
Supun Nakandala, Karla Saur, Gyeong-In Yu, Konstantinos Karanasos, Carlo Curino, Markus Weimer, Matteo Interlandi
2020 J jnl
A Tensor Compiler for Unified Machine Learning Prediction Serving.
CoRR
Supun Nakandala, Karla Saur, Gyeong-In Yu, Konstantinos Karanasos, Carlo Curino, Markus Weimer, Matteo Interlandi
2020 J jnl
Accelerating Multi-Model Inference by Merging DNNs of Different Weights.
CoRR
Joo Seong Jeong, Soojeong Kim, Gyeong-In Yu, Yunseong Lee, Byung-Gon Chun
2020 A* conf
Nimble: Lightweight and Parallel GPU Task Scheduling for Deep Learning.
NeurIPS
Woosuk Kwon, Gyeong-In Yu, Eunji Jeong, Byung-Gon Chun
2020 J jnl
Nimble: Lightweight and Parallel GPU Task Scheduling for Deep Learning.
CoRR
Woosuk Kwon, Gyeong-In Yu, Eunji Jeong, Byung-Gon Chun
2019 A conf
Automating System Configuration of Distributed Machine Learning.
ICDCS
Woo-Yeon Lee, Markus Weimer, Brian Cho, Byung-Gon Chun, Yunseong Lee, Joo Seong Jeong, Gyeong-In Yu, Jooyeon Kim, Hojin Park, Beomyeol Jeon, Won Wook Song, Gunhee Kim
2019 Misc conf
JANUS: Fast and Flexible Deep Learning via Symbolic Graph Execution of Imperative Programs.
NSDI
Eunji Jeong, Sungwoo Cho, Gyeong-In Yu, Joo Seong Jeong, Dongjin Shin, Byung-Gon Chun
2019 J jnl
Making Classical Machine Learning Pipelines Differentiable: A Neural Translation Approach.
CoRR
Gyeong-In Yu, Saeed Amizadeh, Artidoro Pagnoni, Byung-Gon Chun, Markus Weimer, Matteo Interlandi
2019 A conf
Parallax: Sparsity-aware Data Parallel Training of Deep Neural Networks.
EuroSys
Soojeong Kim, Gyeong-In Yu, Hojin Park, Sungwoo Cho, Eunji Jeong, Hyeonmin Ha, Sanha Lee, Joo Seong Jeong, Byung-Gon Chun
2019 J jnl
Speculative Symbolic Graph Execution of Imperative Deep Learning Programs.
ACM SIGOPS Oper. Syst. Rev.
Eunji Jeong, Sungwoo Cho, Gyeong-In Yu, Joo Seong Jeong, Dongjin Shin, Taebum Kim, Byung-Gon Chun
2019 J jnl
Stage-based Hyper-parameter Optimization for Deep Learning.
CoRR
Ahnjae Shin, Dongjin Shin, Sungwoo Cho, Do Yoon Kim, Eunji Jeong, Gyeong-In Yu, Byung-Gon Chun
2018 J jnl
Improving the Expressiveness of Deep Learning Frameworks with Recursion.
CoRR
Eunji Jeong, Joo Seong Jeong, Soojeong Kim, Gyeong-In Yu, Byung-Gon Chun
2018 A conf
Improving the expressiveness of deep learning frameworks with recursion.
EuroSys
Eunji Jeong, Joo Seong Jeong, Soojeong Kim, Gyeong-In Yu, Byung-Gon Chun
2018 J jnl
JANUS: Fast and Flexible Deep Learning via Symbolic Graph Execution of Imperative Programs.
CoRR
Eunji Jeong, Sungwoo Cho, Gyeong-In Yu, Joo Seong Jeong, Dongjin Shin, Byung-Gon Chun
2018 J jnl
Parallax: Automatic Data-Parallel Training of Deep Neural Networks.
CoRR
Soojeong Kim, Gyeong-In Yu, Hojin Park, Sungwoo Cho, Eunji Jeong, Hyeonmin Ha, Sanha Lee, Joo Seong Jeong, Byung-Gon Chun