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Junqi Yin

Publication record assembled from the DBLP archive of ranked conferences.

Papers indexed

15

Venues

5

Active years

2018–2026

Best venue rank

A*

Where they publish

Papers

15 indexed papers, newest first.

YearVenueTitleAuthors
2026ICSFLYING SERVING: On-the-Fly Parallelism Switching for Large Language Model Serving.Shouwei Gao, Junqi Yin, Feiyi Wang, Wenqian Dong
2025ICMLModulated Diffusion: Accelerating Generative Modeling with Modulated Quantization.Weizhi Gao, Zhichao Hou, Junqi Yin, Feiyi Wang, Linyu Peng, Xiaorui Liu
2025SCRingX: Scalable Parallel Attention for Long-Context Learning on HPC.Junqi Yin, Mijanur Palash, Mallikarjun Shankar, Feiyi Wang
2024ICPPThe Case for Co-Designing Model Architectures with Hardware.Quentin Anthony, Jacob Hatef, Deepak Narayanan, Stella Biderman, Stas Bekman, Junqi Yin, Aamir Shafi, Hari Subramoni, Dhabaleswar K. Panda
2024SCSciTrust: Evaluating the Trustworthiness of Large Language Models for Science.Emily J. Herron, Junqi Yin, Feiyi Wang
2024SCEnabling Low-Overhead HT-HPC Workflows at Extreme Scale using GNU Parallel.Ketan Maheshwari, William Arndt, Ahmad Maroof Karimi, Junqi Yin, Frdric Suter, Seth R. Johnson, Rafael Ferreira da Silva
2024SCA Scalable Training-Free Diffusion Model for Uncertainty Quantification.Ali Haisam Muhammad Rafid, Junqi Yin, Yuwei Geng, Siming Liang, Feng Bao, Lili Ju, Guannan Zhang
2024SCORBIT: Oak Ridge Base Foundation Model for Earth System Predictability.Xiao Wang, Siyan Liu, Aristeidis Tsaris, Jong-Youl Choi, Ashwin M. Aji, Ming Fan, Wei Zhang, Junqi Yin, Moetasim Ashfaq, Dan Lu, Prasanna Balaprakash
2024SCA Scalable Real-Time Data Assimilation Framework for Predicting Turbulent Atmosphere Dynamics.Junqi Yin, Siming Liang, Siyan Liu, Feng Bao, Hristo G. Chipilski, Dan Lu, Guannan Zhang
2023SCFORGE: Pre-Training Open Foundation Models for Science.Junqi Yin, Sajal Dash, Feiyi Wang, Mallikarjun Shankar
2022NSDIAccelerating Collective Communication in Data Parallel Training across Deep Learning Frameworks.Joshua Romero, Junqi Yin, Nouamane Laanait, Bing Xie, M. Todd Young, Sean Treichler, Vitalii Starchenko, Albina Y. Borisevich, Alex Sergeev, Michael A. Matheson
2021ICPPIMPECCABLE: Integrated Modeling PipelinE for COVID Cure by Assessing Better LEads.Aymen Al Saadi, Dario Alf, Yadu N. Babuji, Agastya Bhati, Ben Blaiszik, Alexander Brace, Thomas S. Brettin, Kyle Chard, Ryan Chard, Austin Clyde, Peter V. Coveney, Ian T. Foster, Tom Gibbs, Shantenu Jha, Kristopher Keipert, Dieter Kranzlmller, Thorsten Kurth, Hyungro Lee, Zhuozhao Li, Heng Ma, Gerald Mathias, Andr Merzky, Alexander Partin, Arvind Ramanathan, Ashka Shah, Abraham C. Stern, Rick Stevens, Li Tan, Mikhail Titov, Anda Trifan, Aristeidis Tsaris, Matteo Turilli, Huub J. J. Van Dam, Shunzhou Wan, David Wifling, Junqi Yin
2021SCMitigating Catastrophic Forgetting in Deep Learning in a Streaming Setting Using Historical Summary.Sajal Dash, Junqi Yin, Mallikarjun Shankar, Feiyi Wang, Wu-chun Feng
2019SCStrategies to Deploy and Scale Deep Learning on the Summit Supercomputer.Junqi Yin, Shubhankar Gahlot, Nouamane Laanait, Ketan Maheshwari, Jack Morrison, Sajal Dash, Mallikarjun Shankar
2018SCThe design, deployment, and evaluation of the CORAL pre-exascale systems.Sudharshan S. Vazhkudai, Bronis R. de Supinski, Arthur S. Bland, Al Geist, James C. Sexton, Jim Kahle, Christopher Zimmer, Scott Atchley, Sarp Oral, Don E. Maxwell, Vernica G. Vergara Larrea, Adam Bertsch, Robin Goldstone, Wayne Joubert, Chris Chambreau, David Appelhans, Robert Blackmore, Ben Casses, George Chochia, Gene Davison, Matthew A. Ezell, Tom Gooding, Elsa Gonsiorowski, Leopold Grinberg, Bill Hanson, Bill Hartner, Ian Karlin, Matthew L. Leininger, Dustin Leverman, Chris Marroquin, Adam Moody, Martin Ohmacht, Ramesh Pankajakshan, Fernando Pizzano, James H. Rogers, Bryan S. Rosenburg, Drew Schmidt, Mallikarjun Shankar, Feiyi Wang, Py Watson, Bob Walkup, Lance D. Weems, Junqi Yin