Junqi Yin

According to our database, Junqi Yin authored at least 58 papers between 2012 and 2025.

Collaborative distances:

• Dijkstra number of three.
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2025

chatHPC: Empowering HPC users with large language models.

Junqi Yin, Jesse Hines, Emily Herron, Tirthankar Ghosal, Hong Liu, Suzanne Prentice, Vanessa Lama, Feiyi Wang

J. Supercomput., January, 2025

2024

Editorial: Big scientific data analytics on HPC and cloud.

Jianwu Wang, Junqi Yin, Mai H. Nguyen, Jingbo Wang, Weijia Xu

Frontiers Big Data, 2024

A 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

CoRR, 2024

Scalable Artificial Intelligence for Science: Perspectives, Methods and Exemplars.

Wesley Brewer, Aditya Kashi, Sajal Dash, Aristeidis Tsaris, Junqi Yin, Mallikarjun Shankar, Feiyi Wang

CoRR, 2024

Sequence Length Scaling in Vision Transformers for Scientific Images on Frontier.

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

CoRR, 2024

ORBIT: Oak Ridge Base Foundation Model for Earth System Predictability.

Xiao Wang, Aristeidis Tsaris, Siyan Liu, Jong-Youl Choi, Ming Fan, Wei Zhang, Junqi Yin, Moetasim Ashfaq, Dan Lu, Prasanna Balaprakash

CoRR, 2024

Optimizing Distributed Training on Frontier for Large Language Models.

Sajal Dash, Isaac Lyngaas, Junqi Yin, Xiao Wang, Romain Egele, J. Austin Ellis, Matthias Maiterth, Guojing Cong, Feiyi Wang, Prasanna Balaprakash

Proceedings of the ISC High Performance 2024 Research Paper Proceedings (39th International Conference), 2024

Comparative Study of Large Language Model Architectures on Frontier.

Junqi Yin, Avishek Bose, Guojing Cong, Isaac Lyngaas, Quentin Anthony

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2024

Pretraining Billion-Scale Geospatial Foundational Models on Frontier.

Aristeidis Tsaris, Philipe Ambrozio Dias, Abhishek Potnis, Junqi Yin, Feiyi Wang, Dalton D. Lunga

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2024

The 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

Proceedings of the 53rd International Conference on Parallel Processing, 2024

2023

Evaluation of pre-training large language models on leadership-class supercomputers.

Junqi Yin, Sajal Dash, John Gounley, Feiyi Wang, Georgia D. Tourassi

J. Supercomput., December, 2023

Stable parallel training of Wasserstein conditional generative adversarial neural networks.

Massimiliano Lupo Pasini, Junqi Yin

J. Supercomput., 2023

Optimizing Distributed Training on Frontier for Large Language Models.

Sajal Dash, Isaac Lyngaas, Junqi Yin, Xiao Wang, Romain Egele, Guojing Cong, Feiyi Wang, Prasanna Balaprakash

CoRR, 2023

DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies.

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

CoRR, 2023

FORGE: Pre-Training Open Foundation Models for Science.

Junqi Yin, Sajal Dash, Feiyi Wang, Mallikarjun Shankar

Proceedings of the International Conference for High Performance Computing, 2023

DeepThermo: Deep Learning Accelerated Parallel Monte Carlo Sampling for Thermodynamics Evaluation of High Entropy Alloys.

Junqi Yin, Feiyi Wang, Mallikarjun Arjun Shankar

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2023

Distributing Simplex-Shaped Nested for-Loops to Identify Carcinogenic Gene Combinations.

Sajal Dash, Mohammad Alaul Haque Monil, Junqi Yin, Ramu Anandakrishnan, Feiyi Wang

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2023

2022

Atomic structure generation from reconstructing structural fingerprints.

Victor Fung, Shuyi Jia, Jiaxin Zhang, Sirui Bi, Junqi Yin, Panchapakesan Ganesh

Mach. Learn. Sci. Technol., December, 2022

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.

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

Int. J. High Perform. Comput. Appl., 2022

Language models for the prediction of SARS-CoV-2 inhibitors.

Andrew E. Blanchard, John Gounley, Debsindhu Bhowmik, Mayanka Chandra Shekar, Isaac Lyngaas, Shang Gao, Junqi Yin, Aristeidis Tsaris, Feiyi Wang, Jens Glaser

Int. J. High Perform. Comput. Appl., 2022

AI Benchmarking for Science: Efforts from the MLCommons Science Working Group.

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

Proceedings of the High Performance Computing. ISC High Performance 2022 International Workshops - Hamburg, Germany, May 29, 2022

Toward an Autonomous Workflow for Single Crystal Neutron Diffraction.

Junqi Yin, Guannan Zhang, Huibo Cao, Sajal Dash, Bryan C. Chakoumakos, Feiyi Wang

Proceedings of the Accelerating Science and Engineering Discoveries Through Integrated Research Infrastructure for Experiment, Big Data, Modeling and Simulation, 2022

Machine Learning for First Principles Calculations of Material Properties for Ferromagnetic Materials.

Markus Eisenbach, Mariia Karabin, Massimiliano Lupo Pasini, Junqi Yin

Proceedings of the Accelerating Science and Engineering Discoveries Through Integrated Research Infrastructure for Experiment, Big Data, Modeling and Simulation, 2022

Accelerating 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

Proceedings of the 19th USENIX Symposium on Networked Systems Design and Implementation, 2022

Strategies for Integrating Deep Learning Surrogate Models with HPC Simulation Applications.

Junqi Yin, Feiyi Wang, Mallikarjun Shankar

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2022

Learning to Scale the Summit: AI for Science on a Leadership Supercomputer.

Wayne Joubert, Bronson Messer, Philip C. Roth, Antigoni Georgiadou, Justin Lietz, Markus Eisenbach, Junqi Yin

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2022

2021

Scalable balanced training of conditional generative adversarial neural networks on image data.

Massimiliano Lupo Pasini, Vittorio Gabbi, Junqi Yin, Simona Perotto, Nouamane Laanait

J. Supercomput., 2021

A scalable algorithm for the optimization of neural network architectures.

Massimiliano Lupo Pasini, Junqi Yin, Ying Wai Li, Markus Eisenbach

Parallel Comput., 2021

Neural network-based order parameter for phase transitions and its applications in high-entropy alloys.

Junqi Yin, Zongrui Pei, Michael C. Gao

Nat. Comput. Sci., 2021

Dynamic Profiling of β-Coronavirus 3CL Mpro Protease Ligand-Binding Sites.

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

J. Chem. Inf. Model., 2021

Stable Anderson Acceleration for Deep Learning.

Massimiliano Lupo Pasini, Junqi Yin, Viktor Reshniak, Miroslav Stoyanov

CoRR, 2021

MLPerf HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems.

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

CoRR, 2021

Mitigating Catastrophic Forgetting in Deep Learning in a Streaming Setting Using Historical Summary.

Sajal Dash, Junqi Yin, Mallikarjun Shankar, Feiyi Wang, Wu-chun Feng

Proceedings of the 2021 7th International Workshop on Data Analysis and Reduction for Big Scientific Data, 2021

MLPerf™ HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems.

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

Proceedings of the IEEE/ACM Workshop on Machine Learning in High Performance Computing Environments, 2021

Production Deployment of Machine-Learned Rotorcraft Surrogate Models on HPC.

Wesley Brewer, Daniel Martínez, Mathew Boyer, Dylan Jude, Andy Wissink, Ben Parsons, Junqi Yin, Valentine Anantharaj

Proceedings of the IEEE/ACM Workshop on Machine Learning in High Performance Computing Environments, 2021

IMPECCABLE: Integrated Modeling PipelinE for COVID Cure by Assessing Better LEads.

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

Proceedings of the ICPP 2021: 50th International Conference on Parallel Processing, Lemont, IL, USA, August 9, 2021

Stable Parallel Training of Wasserstein Conditional Generative Adversarial Neural Networks : *Full/Regular Research Paper submission for the symposium CSCI-ISAI: Artificial Intelligence.

Massimiliano Lupo Pasini, Junqi Yin

Proceedings of the International Conference on Computational Science and Computational Intelligence, 2021

2020

Deep learning of interface structures from simulated 4D STEM data: cation intermixing vs. roughening.

M. P. Oxley, Junqi Yin, N. Borodinov, Suhas Somnath, Maxim A. Ziatdinov, Andrew R. Lupini, Stephen Jesse, Rama K. Vasudevan, Sergei V. Kalinin

Mach. Learn. Sci. Technol., 2020

Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19.

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

J. Chem. Inf. Model., 2020

Data optimization for large batch distributed training of deep neural networks.

Shubhankar Gahlot, Junqi Yin, Mallikarjun Shankar

CoRR, 2020

Distributed Training and Optimization Of Neural Networks.

Jean-Roch Vlimant, Junqi Yin

CoRR, 2020

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.

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

Proceedings of the Driving Scientific and Engineering Discoveries Through the Convergence of HPC, Big Data and AI, 2020

Toward Real-Time Analysis of Synchrotron Micro-Tomography Data: Accelerating Experimental Workflows with AI and HPC.

James E. McClure, Junqi Yin, Ryan T. Armstrong, Ketan C. Maheshwari, Sean R. Wilkinson, Lucas Vlcek, Ying Da Wang, Mark A. Berrill, Mark Rivers

Proceedings of the Driving Scientific and Engineering Discoveries Through the Convergence of HPC, Big Data and AI, 2020

Performance Evaluation of Python Based Data Analytics Frameworks in Summit: Early Experiences.

Benjamín Hernández, Suhas Somnath, Junqi Yin, Hao Lu, Joe Eaton, Peter Entschev, John Kirkham, Zahra Ronaghi

Proceedings of the Driving Scientific and Engineering Discoveries Through the Convergence of HPC, Big Data and AI, 2020

Integrating Deep Learning in Domain Sciences at Exascale.

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

Proceedings of the Driving Scientific and Engineering Discoveries Through the Convergence of HPC, Big Data and AI, 2020

2019

Exascale Deep Learning for Scientific Inverse Problems.

Nouamane Laanait, Joshua Romero, Junqi Yin, M. Todd Young, Sean Treichler, Vitalii Starchenko, Albina Y. Borisevich, Alex Sergeev, Michael A. Matheson

CoRR, 2019

A greedy constructive algorithm for the optimization of neural network architectures.

Massimiliano Lupo Pasini, Junqi Yin, Ying Wai Li, Markus Eisenbach

CoRR, 2019

Strategies to Deploy and Scale Deep Learning on the Summit Supercomputer.

Junqi Yin, Shubhankar Gahlot, Nouamane Laanait, Ketan Maheshwari, Jack Morrison, Sajal Dash, Mallikarjun Shankar

Proceedings of the Third IEEE/ACM Workshop on Deep Learning on Supercomputers, 2019

2018

Defining Big Data Analytics Benchmarks for Next Generation Supercomputers.

Drew Schmidt, Junqi Yin, Michael A. Matheson, Bronson Messer, Mallikarjun Shankar

CoRR, 2018

The 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, 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

Proceedings of the International Conference for High Performance Computing, 2018

2017

Autumn NDVI contributes more and more to vegetation improvement in the growing season across the Tibetan Plateau.

Jiaqiang Du, Ping He, Shifeng Fang, Weiling Liu, Xinjie Yuan, Junqi Yin

Int. J. Digit. Earth, 2017

2016

Optimization of non-linear image registration in AFNI.

Junqi Yin, Thomas Anthony, Jon Marstrander, Yuliang Liu, Chad Burdyshaw, Mitchel D. Horton, Lonnie D. Crosby, R. Glenn Brook, Frank Skidmore

Proceedings of the XSEDE16 Conference on Diversity, 2016

2015

Analysis on spatio-temporal trends and drivers in vegetation growth during recent decades in Xinjiang, China.

Jiaqiang Du, Jianmin Shu, Junqi Yin, Xinjie Yuan, Jiaerheng Ahati, Shanshan Xiong, Ping He, Weiling Liu

Int. J. Appl. Earth Obs. Geoinformation, 2015

Performance assessment of real-time estimation of continuous-time stochastic volatility of financial data on GPUs.

Daniel Krulewich, Junqi Yin, Brent H. Bundick, Yong Zeng

Proceedings of the 2015 XSEDE Conference: Scientific Advancements Enabled by Enhanced Cyberinfrastructure, St. Louis, MO, USA, July 26, 2015

Integrating apache spark into PBS-Based HPC environments.

Troy Baer, Paul Peltz Jr., Junqi Yin, Edmon Begoli

Proceedings of the 2015 XSEDE Conference: Scientific Advancements Enabled by Enhanced Cyberinfrastructure, St. Louis, MO, USA, July 26, 2015

fMRI image registration with AFNI's 3dQwarp.

Junqi Yin, R. Glenn Brook, Lonnie D. Crosby, Mitchel D. Horton, Chad Burdyshaw, Frank Skidmore, Jon Marstrander, Thomas Anthony, Yuliang Liu

Proceedings of the 6th ACM Conference on Bioinformatics, 2015

2014

Instrumenting Genomic Sequence Analysis Pipeline Mothur on Shared Memory Architecture.

Junqi Yin, Bhanu Rekepalli, Pragneshkumar B. Patel, Chanda Drennen, Annette Summers Engel

Proceedings of the Annual Conference of the Extreme Science and Engineering Discovery Environment, 2014

2012

Massively parallel Wang-Landau sampling on multiple GPUs.

Junqi Yin, D. P. Landau

Comput. Phys. Commun., 2012