Junqi Yin - RankMe

81 papers A* 1A 7B 8C 1Misc 1Journal 45Unranked 18

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	FLYING SERVING: On-the-Fly Parallelism Switching for Large Language Model Serving. CoRR Shouwei Gao, Junqi Yin, Feiyi Wang, Wenqian Dong
2025	J	`jnl`	Decoding Memories: An Efficient Pipeline for Self-Consistency Hallucination Detection. CoRR Weizhi Gao, Xiaorui Liu, Feiyi Wang, Dan Lu, Junqi Yin
2025	A*	`conf`	Modulated Diffusion: Accelerating Generative Modeling with Modulated Quantization. ICML Weizhi Gao, Zhichao Hou, Junqi Yin, Feiyi Wang, Linyu Peng, Xiaorui Liu
2025	J	`jnl`	Modulated Diffusion: Accelerating Generative Modeling with Modulated Quantization. CoRR Weizhi Gao, Zhichao Hou, Junqi Yin, Feiyi Wang, Linyu Peng, Xiaorui Liu
2025	J	`jnl`	Parallel-in-Time Solution of Allen-Cahn Equations by Integrating Operator Learning into the Parareal Method. CoRR Yuwei Geng, Junqi Yin, Eric C. Cyr, Guannan Zhang, Lili Ju
2025	J	`jnl`	Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit. CoRR Junqi Yin, Mijanur Palash, M. Paul Laiu, Muralikrishnan Gopalakrishnan Meena, John Gounley, Stephen M. de Bruyn Kops, Feiyi Wang, Ramanan Sankaran, Pei Zhang
2025	A	`conf`	RingX: Scalable Parallel Attention for Long-Context Learning on HPC. SC Junqi Yin, Mijanur Palash, Mallikarjun Shankar, Feiyi Wang
2025	J	`jnl`	Scaling Up Data Parallelism in Decentralized Deep Learning. CoRR Bing Xie, Junqi Yin, Zhenyu Zhou, Sarp Oral, Feiyi Wang
2025	J	`jnl`	SciTrust 2.0: A Comprehensive Framework for Evaluating Trustworthiness of Large Language Models in Scientific Applications. CoRR Emily Herron, Junqi Yin, Feiyi Wang
2025	J	`jnl`	chatHPC: Empowering HPC users with large language models. J. Supercomput. Junqi Yin, Jesse Hines, Emily Herron, Tirthankar Ghosal, Hong Liu, Suzanne Prentice, Vanessa Lama, Feiyi Wang
2024	—	`conf`	A Scalable Real-Time Data Assimilation Framework for Predicting Turbulent Atmosphere Dynamics. SC Workshops Junqi Yin, Siming Liang, Siyan Liu, Feng Bao, Hristo G. Chipilski, Dan Lu, Guannan Zhang
2024	J	`jnl`	A Scalable Real-Time Data Assimilation Framework for Predicting Turbulent Atmosphere Dynamics. CoRR Junqi Yin, Siming Liang, Siyan Liu, Feng Bao, Hristo G. Chipilski, Dan Lu, Guannan Zhang
2024	—	`conf`	A Scalable Training-Free Diffusion Model for Uncertainty Quantification. SC Workshops Ali Haisam Muhammad Rafid, Junqi Yin, Yuwei Geng, Siming Liang, Feng Bao, Lili Ju, Guannan Zhang
2024	A	`conf`	Comparative Study of Large Language Model Architectures on Frontier. IPDPS Junqi Yin, Avishek Bose, Guojing Cong, Isaac Lyngaas, Quentin Anthony
2024	J	`jnl`	Comparative Study of Large Language Model Architectures on Frontier. CoRR Junqi Yin, Avishek Bose, Guojing Cong, Isaac Lyngaas, Quentin Anthony
2024	J	`jnl`	Editorial: Big scientific data analytics on HPC and cloud. Frontiers Big Data Jianwu Wang, Junqi Yin, Mai H. Nguyen, Jingbo Wang, Weijia Xu
2024	—	`conf`	Enabling Low-Overhead HT-HPC Workflows at Extreme Scale using GNU Parallel. SC Workshops Ketan Maheshwari, William Arndt, Ahmad Maroof Karimi, Junqi Yin, Frédéric Suter, Seth R. Johnson, Rafael Ferreira da Silva
2024	A	`conf`	ORBIT: Oak Ridge Base Foundation Model for Earth System Predictability. SC Xiao Wang, Siyan Liu, Aristeidis Tsaris, Jong-Youl Choi, Ashwin M. Aji, Ming Fan, Wei Zhang, Junqi Yin, Moetasim Ashfaq, Dan Lu, Prasanna Balaprakash
2024	J	`jnl`	ORBIT: Oak Ridge Base Foundation Model for Earth System Predictability. CoRR Xiao Wang, Aristeidis Tsaris, Siyan Liu, Jong-Youl Choi, Ming Fan, Wei Zhang, Junqi Yin, Moetasim Ashfaq, Dan Lu, Prasanna Balaprakash
2024	C	`conf`	Optimizing Distributed Training on Frontier for Large Language Models. ISC Sajal Dash, Isaac Lyngaas, Junqi Yin, Xiao Wang, Romain Egele, J. Austin Ellis, Matthias Maiterth, Guojing Cong, Feiyi Wang, Prasanna Balaprakash
2024	—	`conf`	Pretraining Billion-Scale Geospatial Foundational Models on Frontier. IPDPS (Workshops) Aristeidis Tsaris, Philipe Ambrozio Dias, Abhishek Potnis, Junqi Yin, Feiyi Wang, Dalton D. Lunga
2024	J	`jnl`	Pretraining Billion-scale Geospatial Foundational Models on Frontier. CoRR Aristeidis Tsaris, Philipe Ambrozio Dias, Abhishek Potnis, Junqi Yin, Feiyi Wang, Dalton D. Lunga
2024	J	`jnl`	Scalable Artificial Intelligence for Science: Perspectives, Methods and Exemplars. CoRR Wesley Brewer, Aditya Kashi, Sajal Dash, Aristeidis Tsaris, Junqi Yin, Mallikarjun Shankar, Feiyi Wang
2024	—	`conf`	SciTrust: Evaluating the Trustworthiness of Large Language Models for Science. SC Workshops Emily Herron, Junqi Yin, Feiyi Wang
2024	J	`jnl`	Sequence Length Scaling in Vision Transformers for Scientific Images on Frontier. CoRR Aristeidis Tsaris, Chengming Zhang, Xiao Wang, Junqi Yin, Siyan Liu, Moetasim Ashfaq, Ming Fan, Jong-Youl Choi, Mohamed Wahib, Dan Lu, Prasanna Balaprakash, Fei-Yue Wang
2024	B	`conf`	The Case for Co-Designing Model Architectures with Hardware. ICPP Quentin Anthony, Jacob Hatef, Deepak Narayanan, Stella Biderman, Stas Bekman, Junqi Yin, Aamir Shafi, Hari Subramoni, Dhabaleswar K. Panda
2024	J	`jnl`	The Case for Co-Designing Model Architectures with Hardware. CoRR Quentin Anthony, Jacob Hatef, Deepak Narayanan, Stella Biderman, Stas Bekman, Junqi Yin, Aamir Shafi, Hari Subramoni, Dhabaleswar K. Panda
2023	J	`jnl`	DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies. CoRR Shuaiwen Leon Song, Bonnie Kruft, Minjia Zhang, Conglong Li, Shiyang Chen, Chengming Zhang, Masahiro Tanaka, Xiaoxia Wu, Jeff Rasley, Ammar Ahmad Awan, Connor Holmes, Martin Cai, Adam Ghanem, Zhongzhu Zhou, Yuxiong He, Pete Luferenko, Divya Kumar, Jonathan A. Weyn, Ruixiong Zhang, Sylwester Klocek, Volodymyr Vragov, Mohammed AlQuraishi, Gustaf Ahdritz, Christina Floristean, Cristina Negri, Rao Kotamarthi, Venkatram Vishwanath, Arvind Ramanathan, Sam Foreman, Kyle Hippe, Troy Arcomano, Romit Maulik, Maxim Zvyagin, Alexander Brace, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael W. Irvin, J. Gregory Pauloski, Logan T. Ward, Valérie Hayot-Sasson, Murali Emani, Zhen Xie, Diangen Lin, Maulik Shukla, Ian T. Foster, James J. Davis, Michael E. Papka, Thomas S. Brettin, Prasanna Balaprakash, Gina Tourassi, John Gounley, Heidi A. Hanson, Thomas E. Potok, Massimiliano Lupo Pasini, Kate Evans, Dan Lu, Dalton D. Lunga, Junqi Yin, Sajal Dash, Feiyi Wang, Mallikarjun Shankar, Isaac Lyngaas, Xiao Wang, Guojing Cong, Pei Zhang, Ming Fan, Siyan Liu, Adolfy Hoisie, Shinjae Yoo, Yihui Ren, William Tang, Kyle Felker, Alexey Svyatkovskiy, Hang Liu, Ashwin M. Aji, Angela Dalton, Michael J. Schulte, Karl W. Schulz, Yuntian Deng, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Anima Anandkumar, Rick Stevens
2023	A	`conf`	DeepThermo: Deep Learning Accelerated Parallel Monte Carlo Sampling for Thermodynamics Evaluation of High Entropy Alloys. IPDPS Junqi Yin, Feiyi Wang, Mallikarjun Arjun Shankar
2023	A	`conf`	Distributing Simplex-Shaped Nested for-Loops to Identify Carcinogenic Gene Combinations. IPDPS Sajal Dash, Mohammad Alaul Haque Monil, Junqi Yin, Ramu Anandakrishnan, Feiyi Wang
2023	J	`jnl`	Evaluation of pre-training large language models on leadership-class supercomputers. J. Supercomput. Junqi Yin, Sajal Dash, John Gounley, Feiyi Wang, Georgia D. Tourassi
2023	A	`conf`	FORGE: Pre-Training Open Foundation Models for Science. SC Junqi Yin, Sajal Dash, Feiyi Wang, Mallikarjun Shankar
2023	J	`jnl`	Optimizing Distributed Training on Frontier for Large Language Models. CoRR Sajal Dash, Isaac Lyngaas, Junqi Yin, Xiao Wang, Romain Egele, Guojing Cong, Feiyi Wang, Prasanna Balaprakash
2023	J	`jnl`	Stable parallel training of Wasserstein conditional generative adversarial neural networks. J. Supercomput. Massimiliano Lupo Pasini, Junqi Yin
2022	—	`conf`	AI Benchmarking for Science: Efforts from the MLCommons Science Working Group. ISC Workshops Jeyan Thiyagalingam, Gregor von Laszewski, Junqi Yin, Murali Emani, Juri Papay, Gregg Barrett, Piotr Luszczek, Aristeidis Tsaris, Christine R. Kirkpatrick, Feiyi Wang, Tom Gibbs, Venkatram Vishwanath, Mallikarjun Shankar, Geoffrey C. Fox, Tony Hey
2022	Misc	`conf`	Accelerating Collective Communication in Data Parallel Training across Deep Learning Frameworks. NSDI Joshua Romero, Junqi Yin, Nouamane Laanait, Bing Xie, M. Todd Young, Sean Treichler, Vitalii Starchenko, Albina Y. Borisevich, Alex Sergeev, Michael A. Matheson
2022	J	`jnl`	Atomic structure generation from reconstructing structural fingerprints. CoRR Victor Fung, Shuyi Jia, Jiaxin Zhang, Sirui Bi, Junqi Yin, Panchapakesan Ganesh
2022	J	`jnl`	Atomic structure generation from reconstructing structural fingerprints. Mach. Learn. Sci. Technol. Victor Fung, Shuyi Jia, Jiaxin Zhang, Sirui Bi, Junqi Yin, Panchapakesan Ganesh
2022	J	`jnl`	Intelligent resolution: Integrating Cryo-EM with AI-driven multi-resolution simulations to observe the severe acute respiratory syndrome coronavirus-2 replication-transcription machinery in action. Int. J. High Perform. Comput. Appl. Anda Trifan, Defne Gorgun, Michael Salim, Zongyi Li, Alexander Brace, Maxim Zvyagin, Heng Ma, Austin Clyde, David Clark, David J. Hardy, Tom Burnley, Lei Huang, John D. McCalpin, Murali Emani, Hyenseung Yoo, Junqi Yin, Aristeidis Tsaris, Vishal Subbiah, Tanveer Raza, Jessica Liu, Noah Trebesch, Geoffrey Wells, Venkatesh Mysore, Tom Gibbs, James C. Phillips, S. Chakra Chennubhotla, Ian T. Foster, Rick Stevens, Anima Anandkumar, Venkatram Vishwanath, John E. Stone, Emad Tajkhorshid, Sarah A. Harris, Arvind Ramanathan
2022	J	`jnl`	Language models for the prediction of SARS-CoV-2 inhibitors. Int. J. High Perform. Comput. Appl. Andrew E. Blanchard, John Gounley, Debsindhu Bhowmik, Mayanka Chandra Shekar, Isaac Lyngaas, Shang Gao, Junqi Yin, Aristeidis Tsaris, Feiyi Wang, Jens Glaser
2022	—	`conf`	Learning to Scale the Summit: AI for Science on a Leadership Supercomputer. IPDPS Workshops Wayne Joubert, Bronson Messer, Philip C. Roth, Antigoni Georgiadou, Justin Lietz, Markus Eisenbach, Junqi Yin
2022	B	`conf`	Machine Learning for First Principles Calculations of Material Properties for Ferromagnetic Materials. SMC Markus Eisenbach, Mariia Karabin, Massimiliano Lupo Pasini, Junqi Yin
2022	J	`jnl`	Stable Parallel Training of Wasserstein Conditional Generative Adversarial Neural Networks. CoRR Massimiliano Lupo Pasini, Junqi Yin
2022	—	`conf`	Strategies for Integrating Deep Learning Surrogate Models with HPC Simulation Applications. IPDPS Workshops Junqi Yin, Feiyi Wang, Mallikarjun Shankar
2022	B	`conf`	Toward an Autonomous Workflow for Single Crystal Neutron Diffraction. SMC Junqi Yin, Guannan Zhang, Huibo Cao, Sajal Dash, Bryan C. Chakoumakos, Feiyi Wang
2021	J	`jnl`	A scalable algorithm for the optimization of neural network architectures. Parallel Comput. Massimiliano Lupo Pasini, Junqi Yin, Ying Wai Li, Markus Eisenbach
2021	J	`jnl`	Dynamic Profiling of β-Coronavirus 3CL Mpro Protease Ligand-Binding Sites. J. Chem. Inf. Model. Eunice Cho, Margarida Rosa, Ruhi Anjum, Saman Mehmood, Mariya Soban, Moniza Mujtaba, Khair Bux, Syed Tarique Moin, Mohammad Tanweer, Sarath Chandra Dantu, Alessandro Pandini, Junqi Yin, Heng Ma, Arvind Ramanathan, Barira Islam, Antonia S. J. S. Mey, Debsindhu Bhowmik, Shozeb M. Haider
2021	B	`conf`	IMPECCABLE: Integrated Modeling PipelinE for COVID Cure by Assessing Better LEads. ICPP Aymen Al Saadi, Dario Alfè, 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 Kranzlmüller, Thorsten Kurth, Hyungro Lee, Zhuozhao Li, Heng Ma, Gerald Mathias, André 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
2021	J	`jnl`	MLPerf HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems. CoRR Steven Farrell, Murali Emani, Jacob Balma, Lukas Drescher, Aleksandr Drozd, Andreas Fink, Geoffrey C. Fox, David Kanter, Thorsten Kurth, Peter Mattson, Dawei Mu, Amit Ruhela, Kento Sato, Koichi Shirahata, Tsuguchika Tabaru, Aristeidis Tsaris, Jan Balewski, Ben Cumming, Takumi Danjo, Jens Domke, Takaaki Fukai, Naoto Fukumoto, Tatsuya Fukushi, Balazs Gerofi, Takumi Honda, Toshiyuki Imamura, Akihiko Kasagi, Kentaro Kawakami, Shuhei Kudo, Akiyoshi Kuroda, Maxime Martinasso, Satoshi Matsuoka, Henrique Mendonça, Kazuki Minami, Prabhat Ram, Takashi Sawada, Mallikarjun Shankar, Tom St. John, Akihiro Tabuchi, Venkatram Vishwanath, Mohamed Wahib, Masafumi Yamazaki, Junqi Yin
2021	—	`conf`	MLPerf™ HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems. MLHPC@SC Steven Farrell, Murali Emani, Jacob Balma, Lukas Drescher, Aleksandr Drozd, Andreas Fink, Geoffrey C. Fox, David Kanter, Thorsten Kurth, Peter Mattson, Dawei Mu, Amit Ruhela, Kento Sato, Koichi Shirahata, Tsuguchika Tabaru, Aristeidis Tsaris, Jan Balewski, Ben Cumming, Takumi Danjo, Jens Domke, Takaaki Fukai, Naoto Fukumoto, Tatsuya Fukushi, Balazs Gerofi, Takumi Honda, Toshiyuki Imamura, Akihiko Kasagi, Kentaro Kawakami, Shuhei Kudo, Akiyoshi Kuroda, Maxime Martinasso, Satoshi Matsuoka, Henrique Mendonça, Kazuki Minami, Prabhat Ram, Takashi Sawada, Mallikarjun Shankar, Tom St. John, Akihiro Tabuchi, Venkatram Vishwanath, Mohamed Wahib, Masafumi Yamazaki, Junqi Yin
2021	—	`conf`	Mitigating Catastrophic Forgetting in Deep Learning in a Streaming Setting Using Historical Summary. DRBSD@SC Sajal Dash, Junqi Yin, Mallikarjun Shankar, Feiyi Wang, Wu-chun Feng
2021	J	`jnl`	Neural network based order parameter for phase transitions and its applications in high-entropy alloys. CoRR Junqi Yin, Zongrui Pei, Michael C. Gao
2021	J	`jnl`	Neural network-based order parameter for phase transitions and its applications in high-entropy alloys. Nat. Comput. Sci. Junqi Yin, Zongrui Pei, Michael C. Gao
2021	—	`conf`	Production Deployment of Machine-Learned Rotorcraft Surrogate Models on HPC. MLHPC@SC Wesley Brewer, Daniel Martínez, Mathew Boyer, Dylan Jude, Andy Wissink, Ben Parsons, Junqi Yin, Valentine Anantharaj
2021	J	`jnl`	Scalable Balanced Training of Conditional Generative Adversarial Neural Networks on Image Data. CoRR Massimiliano Lupo Pasini, Vittorio Gabbi, Junqi Yin, Simona Perotto, Nouamane Laanait
2021	J	`jnl`	Scalable balanced training of conditional generative adversarial neural networks on image data. J. Supercomput. Massimiliano Lupo Pasini, Vittorio Gabbi, Junqi Yin, Simona Perotto, Nouamane Laanait
2021	J	`jnl`	Stable Anderson Acceleration for Deep Learning. CoRR Massimiliano Lupo Pasini, Junqi Yin, Viktor Reshniak, Miroslav Stoyanov
2021	—	`conf`	Stable Parallel Training of Wasserstein Conditional Generative Adversarial Neural Networks : *Full/Regular Research Paper submission for the symposium CSCI-ISAI: Artificial Intelligence. CSCI Massimiliano Lupo Pasini, Junqi Yin
2020	J	`jnl`	Data optimization for large batch distributed training of deep neural networks. CoRR Shubhankar Gahlot, Junqi Yin, Mallikarjun Shankar
2020	J	`jnl`	Deep learning of interface structures from simulated 4D STEM data: cation intermixing vs. roughening. Mach. Learn. Sci. Technol. M. P. Oxley, Junqi Yin, N. Borodinov, Suhas Somnath, Maxim A. Ziatdinov, Andrew R. Lupini, Stephen Jesse, Rama K. Vasudevan, Sergei V. Kalinin
2020	J	`jnl`	Distributed Training and Optimization Of Neural Networks. CoRR Jean-Roch Vlimant, Junqi Yin
2020	J	`jnl`	IMPECCABLE: Integrated Modeling PipelinE for COVID Cure by Assessing Better LEads. CoRR Aymen Al Saadi, Dario Alfè, Yadu N. Babuji, Agastya Bhati, Ben Blaiszik, Thomas S. Brettin, Kyle Chard, Ryan Chard, Peter V. Coveney, Anda Trifan, Alex Brace, Austin Clyde, Ian T. Foster, Tom Gibbs, Shantenu Jha, Kristopher Keipert, Thorsten Kurth, Dieter Kranzlmüller, Hyungro Lee, Zhuozhao Li, Heng Ma, André Merzky, Gerald Mathias, Alexander Partin, Junqi Yin, Arvind Ramanathan, Ashka Shah, Abraham C. Stern, Rick Stevens, Li Tan, Mikhail Titov, Aristeidis Tsaris, Matteo Turilli, Huub J. J. Van Dam, Shunzhou Wan, David Wifling
2020	B	`conf`	Integrating Deep Learning in Domain Sciences at Exascale. SMC Rick Archibald, Edmond Chow, Eduardo F. D'Azevedo, Jack J. Dongarra, Markus Eisenbach, Rocco Febbo, Florent Lopez, Daniel Nichols, Stanimire Tomov, Kwai Wong, Junqi Yin
2020	J	`jnl`	Integrating Deep Learning in Domain Sciences at Exascale. CoRR Rick Archibald, Edmond Chow, Eduardo F. D'Azevedo, Jack J. Dongarra, Markus Eisenbach, Rocco Febbo, Florent Lopez, Daniel Nichols, Stanimire Tomov, Kwai Wong, Junqi Yin
2020	B	`conf`	Performance Evaluation of Python Based Data Analytics Frameworks in Summit: Early Experiences. SMC Benjamín Hernández, Suhas Somnath, Junqi Yin, Hao Lu, Joe Eaton, Peter Entschev, John Kirkham, Zahra Ronaghi
2020	B	`conf`	Smoky Mountain Data Challenge 2020: An Open Call to Solve Data Problems in the Areas of Neutron Science, Material Science, Urban Modeling and Dynamics, Geophysics, and Biomedical Informatics. SMC Suzanne Parete-Koon, Peter F. Peterson, Garrett E. Granroth, Wenduo Zhou, Pravallika Devineni, Nouamane Laanait, Junqi Yin, Albina Y. Borisevich, Ketan Maheshwari, Melissa R. Allen-Dumas, Srinath Ravulaparthy, Kuldeep R. Kurte, Jibo Sanyal, Anne Berres, Olivera Kotevska, Folami Alamudun, Keith Gray, Max Grossman, Anar Yusifov, Ioana Danciu, Gil Alterovitz, Dasha Herrmannova
2020	J	`jnl`	Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19. J. Chem. Inf. Model. Atanu Acharya, Rupesh Agarwal, Matthew B. Baker, Jérôme Baudry, Debsindhu Bhowmik, Swen Böhm, Kendall G. Byler, Sam Yen-Chi Chen, Leighton Coates, Connor J. Cooper, Omar Demerdash, Isabella Daidone, John D. Eblen, Sally R. Ellingson, Stefano Forli, Jens Glaser, James C. Gumbart, John Gunnels, Oscar R. Hernandez, Stephan Irle, Daniel W. Kneller, Andrey Kovalevsky, Jeffrey M. Larkin, Travis J. Lawrence, Scott LeGrand, Shih-Hsien Liu, Julie C. Mitchell, Gilchan Park, Jerry M. Parks, Anna Pavlova, Loukas Petridis, Duncan Poole, Line Pouchard, Arvind Ramanathan, David M. Rogers, Diogo Santos-Martins, Aaron Scheinberg, Ada Sedova, Yue Shen, Jeremy C. Smith, Micholas Dean Smith, Carlos Soto, Aristides Tsaris, Mathialakan Thavappiragasam, Andreas F. Tillack, Josh Vincent Vermaas, Van Quan Vuong, Junqi Yin, Shinjae Yoo, Mai Zahran, Laura Zanetti Polzi
2020	B	`conf`	Toward Real-Time Analysis of Synchrotron Micro-Tomography Data: Accelerating Experimental Workflows with AI and HPC. SMC James E. McClure, Junqi Yin, Ryan T. Armstrong, Ketan C. Maheshwari, Sean R. Wilkinson, Lucas Vlcek, Ying Da Wang, Mark A. Berrill, Mark Rivers
2019	J	`jnl`	A greedy constructive algorithm for the optimization of neural network architectures. CoRR Massimiliano Lupo Pasini, Junqi Yin, Ying Wai Li, Markus Eisenbach
2019	J	`jnl`	Exascale Deep Learning for Scientific Inverse Problems. CoRR Nouamane Laanait, Joshua Romero, Junqi Yin, M. Todd Young, Sean Treichler, Vitalii Starchenko, Albina Y. Borisevich, Alex Sergeev, Michael A. Matheson
2019	—	`conf`	Strategies to Deploy and Scale Deep Learning on the Summit Supercomputer. DLS@SC Junqi Yin, Shubhankar Gahlot, Nouamane Laanait, Ketan Maheshwari, Jack Morrison, Sajal Dash, Mallikarjun Shankar
2018	J	`jnl`	Defining Big Data Analytics Benchmarks for Next Generation Supercomputers. CoRR Drew Schmidt, Junqi Yin, Michael A. Matheson, Bronson Messer, Mallikarjun Shankar
2018	A	`conf`	The design, deployment, and evaluation of the CORAL pre-exascale systems. SC 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, Verónica 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
2017	J	`jnl`	Autumn NDVI contributes more and more to vegetation improvement in the growing season across the Tibetan Plateau. Int. J. Digit. Earth Jiaqiang Du, Ping He, Shifeng Fang, Weiling Liu, Xinjie Yuan, Junqi Yin
2016	—	`conf`	Optimization of non-linear image registration in AFNI. XSEDE Junqi Yin, Thomas Anthony, Jon Marstrander, Yuliang Liu, Chad Burdyshaw, Mitchel D. Horton, Lonnie D. Crosby, R. Glenn Brook, Frank Skidmore
2015	J	`jnl`	Analysis on spatio-temporal trends and drivers in vegetation growth during recent decades in Xinjiang, China. Int. J. Appl. Earth Obs. Geoinformation Jiaqiang Du, Jianmin Shu, Junqi Yin, Xinjie Yuan, Jiaerheng Ahati, Shanshan Xiong, Ping He, Weiling Liu
2015	—	`conf`	Integrating apache spark into PBS-Based HPC environments. XSEDE Troy Baer, Paul Peltz Jr., Junqi Yin, Edmon Begoli
2015	—	`conf`	Performance assessment of real-time estimation of continuous-time stochastic volatility of financial data on GPUs. XSEDE Daniel Krulewich, Junqi Yin, Brent H. Bundick, Yong Zeng
2015	—	`conf`	fMRI image registration with AFNI's 3dQwarp. BCB Junqi Yin, R. Glenn Brook, Lonnie D. Crosby, Mitchel D. Horton, Chad Burdyshaw, Frank Skidmore, Jon Marstrander, Thomas Anthony, Yuliang Liu
2014	—	`conf`	Instrumenting Genomic Sequence Analysis Pipeline Mothur on Shared Memory Architecture. XSEDE Junqi Yin, Bhanu Rekepalli, Pragneshkumar B. Patel, Chanda Drennen, Annette Summers Engel
2012	J	`jnl`	Massively parallel Wang-Landau sampling on multiple GPUs. Comput. Phys. Commun. Junqi Yin, D. P. Landau