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Joo Seong Jeong
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2020 – today
- 2022
- [j3]Ahnjae Shin, Joo Seong Jeong, Do Yoon Kim, Soyoung Jung, Byung-Gon Chun:
Hippo: Sharing Computations in Hyper-Parameter Optimization. Proc. VLDB Endow. 15(5): 1038-1052 (2022) - [c7]Joo Seong Jeong, Jingyu Lee, Donghyun Kim, Changmin Jeon, Changjin Jeong, Youngki Lee, Byung-Gon Chun:
Band: coordinated multi-DNN inference on heterogeneous mobile processors. MobiSys 2022: 235-247 - [c6]Gyeong-In Yu, Joo Seong Jeong, Geon-Woo Kim, Soojeong Kim, Byung-Gon Chun:
Orca: A Distributed Serving System for Transformer-Based Generative Models. OSDI 2022: 521-538 - 2020
- [i5]Ahnjae Shin, Do Yoon Kim, Joo Seong Jeong, Byung-Gon Chun:
Hippo: Taming Hyper-parameter Optimization of Deep Learning with Stage Trees. CoRR abs/2006.11972 (2020) - [i4]Joo Seong Jeong, Soojeong Kim, Gyeong-In Yu, Yunseong Lee, Byung-Gon Chun:
Accelerating Multi-Model Inference by Merging DNNs of Different Weights. CoRR abs/2009.13062 (2020)
2010 – 2019
- 2019
- [j2]Eunji Jeong, Sungwoo Cho, Gyeong-In Yu, Joo Seong Jeong, Dongjin Shin, Taebum Kim, Byung-Gon Chun:
Speculative Symbolic Graph Execution of Imperative Deep Learning Programs. ACM SIGOPS Oper. Syst. Rev. 53(1): 26-33 (2019) - [c5]Soojeong Kim, Gyeong-In Yu, Hojin Park, Sungwoo Cho, Eunji Jeong, Hyeonmin Ha, Sanha Lee, Joo Seong Jeong, Byung-Gon Chun:
Parallax: Sparsity-aware Data Parallel Training of Deep Neural Networks. EuroSys 2019: 43:1-43:15 - [c4]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:
Automating System Configuration of Distributed Machine Learning. ICDCS 2019: 2057-2067 - [c3]Eunji Jeong, Sungwoo Cho, Gyeong-In Yu, Joo Seong Jeong, Dongjin Shin, Byung-Gon Chun:
JANUS: Fast and Flexible Deep Learning via Symbolic Graph Execution of Imperative Programs. NSDI 2019: 453-468 - 2018
- [c2]Eunji Jeong, Joo Seong Jeong, Soojeong Kim, Gyeong-In Yu, Byung-Gon Chun:
Improving the expressiveness of deep learning frameworks with recursion. EuroSys 2018: 19:1-19:13 - [i3]Soojeong Kim, Gyeong-In Yu, Hojin Park, Sungwoo Cho, Eunji Jeong, Hyeonmin Ha, Sanha Lee, Joo Seong Jeong, Byung-Gon Chun:
Parallax: Automatic Data-Parallel Training of Deep Neural Networks. CoRR abs/1808.02621 (2018) - [i2]Eunji Jeong, Joo Seong Jeong, Soojeong Kim, Gyeong-In Yu, Byung-Gon Chun:
Improving the Expressiveness of Deep Learning Frameworks with Recursion. CoRR abs/1809.00832 (2018) - [i1]Eunji Jeong, Sungwoo Cho, Gyeong-In Yu, Joo Seong Jeong, Dongjin Shin, Byung-Gon Chun:
JANUS: Fast and Flexible Deep Learning via Symbolic Graph Execution of Imperative Programs. CoRR abs/1812.01329 (2018) - 2017
- [j1]Byung-Gon Chun, Tyson Condie, Yingda Chen, Brian Cho, Andrew Chung, Carlo Curino, Chris Douglas, Matteo Interlandi, Beomyeol Jeon, Joo Seong Jeong, Gyewon Lee, Yunseong Lee, Tony Majestro, Dahlia Malkhi, Sergiy Matusevych, Brandon Myers, Mariia Mykhailova, Shravan M. Narayanamurthy, Joseph Noor, Raghu Ramakrishnan, Sriram Rao, Russell Sears, Beysim Sezgin, Taegeon Um, Julia Wang, Markus Weimer, Youngseok Yang:
Apache REEF: Retainable Evaluator Execution Framework. ACM Trans. Comput. Syst. 35(2): 5:1-5:31 (2017) - 2015
- [c1]Joo Seong Jeong, Woo-Yeon Lee, Yunseong Lee, Youngseok Yang, Brian Cho, Byung-Gon Chun:
Elastic Memory: Bring Elasticity Back to In-Memory Big Data Analytics. HotOS 2015
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