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2020 – today
- 2025
[j16]Junqi Yin, Jesse Hines, Emily Herron, Tirthankar Ghosal, Hong Liu, Suzanne Prentice, Vanessa Lama, Feiyi Wang:
chatHPC: Empowering HPC users with large language models. J. Supercomput. 81(1): 194 (2025)- 2024
- [j15]Jianwu Wang, Junqi Yin, Mai H. Nguyen, Jingbo Wang, Weijia Xu:
Editorial: Big scientific data analytics on HPC and cloud. Frontiers Big Data 7 (2024) - [c30]Quentin Anthony
, Jacob Hatef, Deepak Narayanan, Stella Biderman, Stas Bekman, Junqi Yin, Aamir Shafi, Hari Subramoni, Dhabaleswar K. Panda:
The Case for Co-Designing Model Architectures with Hardware. ICPP 2024: 84-96 - [c29]Junqi Yin, Avishek Bose, Guojing Cong, Isaac Lyngaas, Quentin Anthony:
Comparative Study of Large Language Model Architectures on Frontier. IPDPS 2024: 556-569 - [c28]Aristeidis Tsaris, Philipe Ambrozio Dias, Abhishek Potnis, Junqi Yin, Feiyi Wang, Dalton D. Lunga:
Pretraining Billion-Scale Geospatial Foundational Models on Frontier. IPDPS (Workshops) 2024: 1036-1046 - [c27]Xiao Wang, Siyan Liu, Aristeidis Tsaris, Jong-Youl Choi, Ashwin M. Aji, Ming Fan, Wei Zhang, Junqi Yin, Moetasim Ashfaq, Dan Lu, Prasanna Balaprakash:
ORBIT: Oak Ridge Base Foundation Model for Earth System Predictability. SC 2024: 1 - [c26]Sajal Dash, Isaac Lyngaas, Junqi Yin, Xiao Wang, Romain Egele, J. Austin Ellis, Matthias Maiterth, Guojing Cong, Feiyi Wang, Prasanna Balaprakash:
Optimizing Distributed Training on Frontier for Large Language Models. ISC 2024: 1-11 - [i22]Quentin Anthony, Jacob Hatef, Deepak Narayanan, Stella Biderman, Stas Bekman, Junqi Yin, Aamir Shafi, Hari Subramoni, Dhabaleswar K. Panda:
The Case for Co-Designing Model Architectures with Hardware. CoRR abs/2401.14489 (2024) - [i21]Junqi Yin, Avishek Bose, Guojing Cong, Isaac Lyngaas, Quentin Anthony:
Comparative Study of Large Language Model Architectures on Frontier. CoRR abs/2402.00691 (2024) - [i20]Aristeidis Tsaris, Philipe Ambrozio Dias, Abhishek Potnis, Junqi Yin, Feiyi Wang, Dalton D. Lunga:
Pretraining Billion-scale Geospatial Foundational Models on Frontier. CoRR abs/2404.11706 (2024) - [i19]Xiao Wang, Aristeidis Tsaris, Siyan Liu, Jong-Youl Choi, Ming Fan, Wei Zhang, Junqi Yin, Moetasim Ashfaq, Dan Lu, Prasanna Balaprakash:
ORBIT: Oak Ridge Base Foundation Model for Earth System Predictability. CoRR abs/2404.14712 (2024) - [i18]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:
Sequence Length Scaling in Vision Transformers for Scientific Images on Frontier. CoRR abs/2405.15780 (2024) - [i17]Wesley Brewer, Aditya Kashi, Sajal Dash, Aristeidis Tsaris, Junqi Yin, Mallikarjun Shankar, Feiyi Wang:
Scalable Artificial Intelligence for Science: Perspectives, Methods and Exemplars. CoRR abs/2406.17812 (2024) - [i16]Junqi Yin, Siming Liang, Siyan Liu, Feng Bao, Hristo G. Chipilski, Dan Lu, Guannan Zhang:
A Scalable Real-Time Data Assimilation Framework for Predicting Turbulent Atmosphere Dynamics. CoRR abs/2407.12168 (2024) - 2023
- [j14]Massimiliano Lupo Pasini, Junqi Yin:
Stable parallel training of Wasserstein conditional generative adversarial neural networks. J. Supercomput. 79(2): 1856-1876 (2023) - [j13]Junqi Yin, Sajal Dash, John Gounley, Feiyi Wang, Georgia D. Tourassi:
Evaluation of pre-training large language models on leadership-class supercomputers. J. Supercomput. 79(18): 20747-20768 (2023) - [c25]Junqi Yin, Feiyi Wang, Mallikarjun Arjun Shankar:
DeepThermo: Deep Learning Accelerated Parallel Monte Carlo Sampling for Thermodynamics Evaluation of High Entropy Alloys. IPDPS 2023: 333-343 - [c24]Sajal Dash, Mohammad Alaul Haque Monil, Junqi Yin, Ramu Anandakrishnan, Feiyi Wang:
Distributing Simplex-Shaped Nested for-Loops to Identify Carcinogenic Gene Combinations. IPDPS 2023: 974-984 - [c23]Junqi Yin, Sajal Dash, Feiyi Wang, Mallikarjun Shankar:
FORGE: Pre-Training Open Foundation Models for Science. SC 2023: 81:1-81:13 - [i15]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 Schulz, Yuntian Deng, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Anima Anandkumar, Rick Stevens:
DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies. CoRR abs/2310.04610 (2023) - [i14]Sajal Dash, Isaac Lyngaas, Junqi Yin, Xiao Wang, Romain Egele, Guojing Cong, Feiyi Wang, Prasanna Balaprakash:
Optimizing Distributed Training on Frontier for Large Language Models. CoRR abs/2312.12705 (2023) - 2022
- [j12]Andrew E. Blanchard, John Gounley, Debsindhu Bhowmik, Mayanka Chandra Shekar, Isaac Lyngaas, Shang Gao, Junqi Yin, Aristeidis Tsaris, Feiyi Wang, Jens Glaser:
Language models for the prediction of SARS-CoV-2 inhibitors. Int. J. High Perform. Comput. Appl. 36(5-6): 587-602 (2022) - [j11]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:
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. 36(5-6): 603-623 (2022) - [j10]Victor Fung, Shuyi Jia, Jiaxin Zhang, Sirui Bi, Junqi Yin, Panchapakesan Ganesh:
Atomic structure generation from reconstructing structural fingerprints. Mach. Learn. Sci. Technol. 3(4): 45018 (2022) - [c22]Junqi Yin, Feiyi Wang, Mallikarjun Shankar:
Strategies for Integrating Deep Learning Surrogate Models with HPC Simulation Applications. IPDPS Workshops 2022: 1-10 - [c21]Wayne Joubert, Bronson Messer, Philip C. Roth, Antigoni Georgiadou, Justin Lietz, Markus Eisenbach, Junqi Yin:
Learning to Scale the Summit: AI for Science on a Leadership Supercomputer. IPDPS Workshops 2022: 1246-1255 - [c20]Joshua Romero, Junqi Yin, Nouamane Laanait, Bing Xie, M. Todd Young, Sean Treichler, Vitalii Starchenko, Albina Y. Borisevich, Alex Sergeev, Michael A. Matheson:
Accelerating Collective Communication in Data Parallel Training across Deep Learning Frameworks. NSDI 2022: 1027-1040 - [c19]Markus Eisenbach, Mariia Karabin, Massimiliano Lupo Pasini, Junqi Yin:
Machine Learning for First Principles Calculations of Material Properties for Ferromagnetic Materials. SMC 2022: 75-86 - [c18]Junqi Yin, Guannan Zhang, Huibo Cao, Sajal Dash, Bryan C. Chakoumakos, Feiyi Wang:
Toward an Autonomous Workflow for Single Crystal Neutron Diffraction. SMC 2022: 244-256 - [c17]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:
AI Benchmarking for Science: Efforts from the MLCommons Science Working Group. ISC Workshops 2022: 47-64 - [i13]Massimiliano Lupo Pasini, Junqi Yin:
Stable Parallel Training of Wasserstein Conditional Generative Adversarial Neural Networks. CoRR abs/2207.12315 (2022) - [i12]Victor Fung, Shuyi Jia, Jiaxin Zhang, Sirui Bi, Junqi Yin, Panchapakesan Ganesh:
Atomic structure generation from reconstructing structural fingerprints. CoRR abs/2207.13227 (2022) - 2021
- [j9]Eunice Cho, Margarida Rosa, Ruhi Anjum, Saman Mehmood, Mariya Soban, Moniza Mujtaba, Khair Bux, Syed Tarique Moin, Mohammad Tanweer, Sarath Dantu, Alessandro Pandini, Junqi Yin, Heng Ma, Arvind Ramanathan, Barira Islam, Antonia S. J. S. Mey, Debsindhu Bhowmik, Shozeb M. Haider:
Dynamic Profiling of β-Coronavirus 3CL Mpro Protease Ligand-Binding Sites. J. Chem. Inf. Model. 61(6): 3058-3073 (2021) - [j8]Junqi Yin, Zongrui Pei, Michael C. Gao:
Neural network-based order parameter for phase transitions and its applications in high-entropy alloys. Nat. Comput. Sci. 1(10): 686-693 (2021) - [j7]Massimiliano Lupo Pasini, Junqi Yin, Ying Wai Li, Markus Eisenbach:
A scalable algorithm for the optimization of neural network architectures. Parallel Comput. 104-105: 102788 (2021) - [j6]Massimiliano Lupo Pasini, Vittorio Gabbi, Junqi Yin, Simona Perotto, Nouamane Laanait:
Scalable balanced training of conditional generative adversarial neural networks on image data. J. Supercomput. 77(11): 13358-13384 (2021) - [c16]Massimiliano Lupo Pasini, Junqi Yin:
Stable Parallel Training of Wasserstein Conditional Generative Adversarial Neural Networks : *Full/Regular Research Paper submission for the symposium CSCI-ISAI: Artificial Intelligence. CSCI 2021: 1-7 - [c15]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:
IMPECCABLE: Integrated Modeling PipelinE for COVID Cure by Assessing Better LEads. ICPP 2021: 40:1-40:12 - [c14]Wesley Brewer, Daniel Martínez, Mathew Boyer, Dylan Jude, Andy Wissink, Ben Parsons, Junqi Yin, Valentine Anantharaj:
Production Deployment of Machine-Learned Rotorcraft Surrogate Models on HPC. MLHPC@SC 2021: 21-32 - [c13]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:
MLPerf™ HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems. MLHPC@SC 2021: 33-45 - [c12]Sajal Dash, Junqi Yin, Mallikarjun Shankar, Feiyi Wang, Wu-chun Feng:
Mitigating Catastrophic Forgetting in Deep Learning in a Streaming Setting Using Historical Summary. DRBSD@SC 2021: 11-18 - [i11]Massimiliano Lupo Pasini, Vittorio Gabbi, Junqi Yin, Simona Perotto, Nouamane Laanait:
Scalable Balanced Training of Conditional Generative Adversarial Neural Networks on Image Data. CoRR abs/2102.10485 (2021) - [i10]Junqi Yin, Zongrui Pei, Michael C. Gao:
Neural network based order parameter for phase transitions and its applications in high-entropy alloys. CoRR abs/2109.05598 (2021) - [i9]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:
MLPerf HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems. CoRR abs/2110.11466 (2021) - [i8]Massimiliano Lupo Pasini, Junqi Yin, Viktor Reshniak, Miroslav Stoyanov:
Stable Anderson Acceleration for Deep Learning. CoRR abs/2110.14813 (2021) - 2020
- [j5]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:
Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19. J. Chem. Inf. Model. 60(12): 5832-5852 (2020) - [j4]M. P. Oxley, Junqi Yin, N. Borodinov, Suhas Somnath, Maxim A. Ziatdinov, Andrew R. Lupini, Stephen Jesse, Rama K. Vasudevan, Sergei V. Kalinin:
Deep learning of interface structures from simulated 4D STEM data: cation intermixing vs. roughening. Mach. Learn. Sci. Technol. 1(4): 04 (2020) - [c11]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:
Integrating Deep Learning in Domain Sciences at Exascale. SMC 2020: 35-50 - [c10]James E. McClure, Junqi Yin, Ryan T. Armstrong, Ketan C. Maheshwari, Sean R. Wilkinson, Lucas Vlcek, Ying Da Wang, Mark A. Berrill, Mark Rivers:
Toward Real-Time Analysis of Synchrotron Micro-Tomography Data: Accelerating Experimental Workflows with AI and HPC. SMC 2020: 226-239 - [c9]Benjamín Hernández, Suhas Somnath, Junqi Yin, Hao Lu, Joe Eaton, Peter Entschev, John Kirkham, Zahra Ronaghi:
Performance Evaluation of Python Based Data Analytics Frameworks in Summit: Early Experiences. SMC 2020: 366-380 - [c8]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:
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 2020: 425-442 - [i7]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:
IMPECCABLE: Integrated Modeling PipelinE for COVID Cure by Assessing Better LEads. CoRR abs/2010.06574 (2020) - [i6]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:
Integrating Deep Learning in Domain Sciences at Exascale. CoRR abs/2011.11188 (2020) - [i5]Jean-Roch Vlimant, Junqi Yin:
Distributed Training and Optimization Of Neural Networks. CoRR abs/2012.01839 (2020) - [i4]Shubhankar Gahlot, Junqi Yin, Mallikarjun Shankar:
Data optimization for large batch distributed training of deep neural networks. CoRR abs/2012.09272 (2020)
2010 – 2019
- 2019
- [c7]Junqi Yin, Shubhankar Gahlot, Nouamane Laanait, Ketan Maheshwari, Jack Morrison, Sajal Dash, Mallikarjun Shankar:
Strategies to Deploy and Scale Deep Learning on the Summit Supercomputer. DLS@SC 2019: 84-94 - [i3]Massimiliano Lupo Pasini, Junqi Yin, Ying Wai Li, Markus Eisenbach:
A greedy constructive algorithm for the optimization of neural network architectures. CoRR abs/1909.03306 (2019) - [i2]Nouamane Laanait, Joshua Romero, Junqi Yin, M. Todd Young, Sean Treichler, Vitalii Starchenko, Albina Y. Borisevich, Alex Sergeev, Michael A. Matheson:
Exascale Deep Learning for Scientific Inverse Problems. CoRR abs/1909.11150 (2019) - 2018
- [c6]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:
The design, deployment, and evaluation of the CORAL pre-exascale systems. SC 2018: 52:1-52:12 - [i1]Drew Schmidt, Junqi Yin, Michael A. Matheson, Bronson Messer, Mallikarjun Shankar:
Defining Big Data Analytics Benchmarks for Next Generation Supercomputers. CoRR abs/1811.02287 (2018) - 2017
- [j3]Jiaqiang Du, Ping He, Shifeng Fang, Weiling Liu, Xinjie Yuan, Junqi Yin:
Autumn NDVI contributes more and more to vegetation improvement in the growing season across the Tibetan Plateau. Int. J. Digit. Earth 10(11): 1098-1117 (2017) - 2016
- [c5]Junqi Yin, Thomas Anthony, Jon Marstrander, Yuliang Liu, Chad Burdyshaw, Mitchel D. Horton, Lonnie D. Crosby, R. Glenn Brook, Frank Skidmore:
Optimization of non-linear image registration in AFNI. XSEDE 2016: 6:1-6:6 - 2015
- [j2]Jiaqiang Du, Jianmin Shu, Junqi Yin, Xinjie Yuan, Jiaerheng Ahati, Shanshan Xiong, Ping He, Weiling Liu:
Analysis on spatio-temporal trends and drivers in vegetation growth during recent decades in Xinjiang, China. Int. J. Appl. Earth Obs. Geoinformation 38: 216-228 (2015) - [c4]Junqi Yin, R. Glenn Brook, Lonnie D. Crosby, Mitchel D. Horton, Chad Burdyshaw, Frank Skidmore, Jon Marstrander, Thomas Anthony, Yuliang Liu:
fMRI image registration with AFNI's 3dQwarp. BCB 2015: 559-560 - [c3]Daniel Krulewich, Junqi Yin, Brent H. Bundick, Yong Zeng:
Performance assessment of real-time estimation of continuous-time stochastic volatility of financial data on GPUs. XSEDE 2015: 9:1-9:4 - [c2]Troy Baer, Paul Peltz Jr., Junqi Yin, Edmon Begoli:
Integrating apache spark into PBS-Based HPC environments. XSEDE 2015: 34:1-34:7 - 2014
- [c1]Junqi Yin, Bhanu Rekepalli, Pragneshkumar B. Patel, Chanda Drennen, Annette Summers Engel:
Instrumenting Genomic Sequence Analysis Pipeline Mothur on Shared Memory Architecture. XSEDE 2014: 19:1-19:4 - 2012
- [j1]Junqi Yin, D. P. Landau:
Massively parallel Wang-Landau sampling on multiple GPUs. Comput. Phys. Commun. 183(8): 1568-1573 (2012)
Coauthor Index
Mallikarjun Shankar
aka: Mallikarjun Arjun Shankar
aka: Mallikarjun Arjun Shankar
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