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Bio
I am also interested in designing large-scale distributed systems for training machine learning applications. To that end, I led the development of a massively large-scale distributed reinforcement learning system that scales to TPU Pod and efficiently manages thousands of actors to solve complex, real-world tasks. As a case study, our team demonstrates how using this highly scalable system enables reinforcement learning to accomplish chip placement in ~an hour instead of days or weeks by human effort.
Research Interests
Papers共 87 篇Author StatisticsCo-AuthorSimilar Experts
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Proceedings of the ACM on Measurement and Analysis of Computing Systemsno. 2 (2024): 1-25
Yoonsung Kim, Changhun Oh,Jinwoo Hwang, Wonung Kim, Seongryong Oh, Yubin Lee,Hardik Sharma,Amir Yazdanbakhsh,Jongse Park
CoRR (2024)
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IEEE Comput. Archit. Lett.no. 1 (2024): 117-120
Soroush Ghodrati,Sean Kinzer,Hanyang Xu,Rohan Mahapatra, Yoonsung Kim,Byung Hoon Ahn,Dong Kai Wang, Lavanya Karthikeyan,Amir Yazdanbakhsh,Jongse Park,Nam Sung Kim,Hadi Esmaeilzadeh
Simla Burcu Harma, Ayan Chakraborty, Elizaveta Kostenok, Danila Mishin, Dongho Ha,Babak Falsafi,Martin Jaggi, Ming Liu,Yunho Oh,Suvinay Subramanian,Amir Yazdanbakhsh
CoRR (2024)
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CoRR (2024)
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PROCEEDINGS OF THE 2023 THE 50TH ANNUAL INTERNATIONAL SYMPOSIUM ON COMPUTER ARCHITECTURE, ISCA 2023 (2023): 186-201
DACpp.1-2, (2023)
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