Logan T. Ward

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 34

Top Topics

Service Platform

Named Entity Recognition

Scientific Discovery

Top Venues

WOSC@Middleware

Publications

K. J. Schmidt, Aristana Scourtas, Logan T. Ward, Steve Wangen, Marcus Schwarting, Isaac Darling, Ethan Truelove, Aadit Ambadkar, Ribhav Bose, Zoa Katok, Jingrui Wei, Xiangguo Li, Ryan Jacobs, Lane Schultz, Doyeon Kim, Michael C. Ferris, Paul M. Voyles, Dane Morgan, Ian Foster, Ben Blaiszik
Foundry-ML - Software and Services to Simplify Access to Machine Learning Datasets in Materials Science. J. Open Source Softw. 9 (93) (2024)
Andrew S. Lee, Sarah Elliott, Hassan Harb, Logan T. Ward, Ian T. Foster, Larry A. Curtiss, Rajeev S. Assary
: A First-Principles Thermochemical Descriptor for Predicting Molecular Synthesizability. J. Chem. Inf. Model. 64 (4) (2024)
Nathaniel Hudson, J. Gregory Pauloski, Matt Baughman, Alok Kamatar, Mansi Sakarvadia, Logan T. Ward, Ryan Chard, André Bauer, Maksim Levental, Wenyi Wang, Will Engler, Owen Price Skelly, Ben Blaiszik, Rick Stevens, Kyle Chard, Ian T. Foster
Trillion Parameter AI Serving Infrastructure for Scientific Discovery: A Survey and Vision. CoRR (2024)
J. Gregory Pauloski, Valérie Hayot-Sasson, Logan T. Ward, Alexander Brace, André Bauer, Kyle Chard, Ian T. Foster
Object Proxy Patterns for Accelerating Distributed Applications. CoRR (2024)
J. Gregory Pauloski, Valérie Hayot-Sasson, Logan T. Ward, Nathaniel Hudson, Charlie Sabino, Matt Baughman, Kyle Chard, Ian T. Foster
Accelerating Communications in Federated Applications with Transparent Object Proxies. CoRR (2023)
Logan T. Ward, Ben Blaiszik, Cheng-Wei Lee, Troy Martin, Ian T. Foster, André Schleife
Accelerating Electronic Stopping Power Predictions by 10 Million Times with a Combination of Time-Dependent Density Functional Theory and Machine Learning. CoRR (2023)
Logan T. Ward, J. Gregory Pauloski, Valérie Hayot-Sasson, Ryan Chard, Yadu N. Babuji, Ganesh Sivaraman, Sutanay Choudhury, Kyle Chard, Rajeev Thakur, Ian T. Foster
Cloud Services Enable Efficient AI-Guided Simulation Workflows across Heterogeneous Resources. CoRR (2023)
Nathaniel Hudson, J. Gregory Pauloski, Matt Baughman, Alok Kamatar, Mansi Sakarvadia, Logan T. Ward, Ryan Chard, André Bauer, Maksim Levental, Wenyi Wang, Will Engler, Owen Price Skelly, Ben Blaiszik, Rick Stevens, Kyle Chard, Ian T. Foster
Trillion Parameter AI Serving Infrastructure for Scientific Discovery: A Survey and Vision. BDCAT (2023)
J. Gregory Pauloski, Valérie Hayot-Sasson, Logan T. Ward, Nathaniel Hudson, Charlie Sabino, Matt Baughman, Kyle Chard, Ian T. Foster
Accelerating Communications in Federated Applications with Transparent Object Proxies. SC (2023)
Aditya Dhakal, Philipp Raith, Logan T. Ward, Rolando P. Hong Enriquez, Gourav Rattihalli, Kyle Chard, Ian T. Foster, Dejan S. Milojicic
Fine-grained accelerator partitioning for Machine Learning and Scientific Computing in Function as a Service Platform. SC Workshops (2023)
Logan T. Ward, J. Gregory Pauloski, Valérie Hayot-Sasson, Ryan Chard, Yadu N. Babuji, Ganesh Sivaraman, Sutanay Choudhury, Kyle Chard, Rajeev Thakur, Ian T. Foster
Cloud Services Enable Efficient AI-Guided Simulation Workflows across Heterogeneous Resources. IPDPS Workshops (2023)
Kevin Maik Jablonka, Qianxiang Ai, Alexander Al-Feghali, Shruti Badhwar, Joshua D. Bocarsly Andres M. Bran, Stefan Bringuier, L. Catherine Brinson, Kamal Choudhary, Defne Circi, Sam Cox, Wibe A. de Jong, Matthew L. Evans, Nicolas Gastellu, Jerome Genzling, María Victoria Gil, Ankur K. Gupta, Zhi Hong, Alishba Imran, Sabine Kruschwitz, Anne Labarre, Jakub Lála, Tao Liu, Steven Ma, Sauradeep Majumdar, Garrett W. Merz, Nicolas Moitessier, Elias Moubarak, Beatriz Mouriño, Brenden Pelkie, Michael Pieler, Mayk Caldas Ramos, Bojana Rankovic, Samuel G. Rodriques, Jacob N. Sanders, Philippe Schwaller, Marcus Schwarting, Jiale Shi, Berend Smit, Ben E. Smith, Joren Van Heck, Christoph Völker, Logan T. Ward, Sean Warren, Benjamin Weiser, Sylvester Zhang, Xiaoqi Zhang, Ghezal Ahmad Zia, Aristana Scourtas, K. J. Schmidt, Ian T. Foster, Andrew D. White, Ben Blaiszik
14 Examples of How LLMs Can Transform Materials Science and Chemistry: A Reflection on a Large Language Model Hackathon. CoRR (2023)
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 (2023)
Aymen Alsaadi, Logan T. Ward, André Merzky, Kyle Chard, Ian T. Foster, Shantenu Jha, Matteo Turilli
RADICAL-Pilot and Parsl: Executing Heterogeneous Workflows on HPC Platforms. WORKS@SC (2022)
Yuliana Zamora, Logan T. Ward, Ganesh Sivaraman, Ian T. Foster, Henry Hoffmann
Proxima: accelerating the integration of machine learning in atomistic simulations. ICS (2021)
Logan T. Ward, Ganesh Sivaraman, J. Gregory Pauloski, Yadu N. Babuji, Ryan Chard, Naveen Dandu, Paul C. Redfern, Rajeev S. Assary, Kyle Chard, Larry A. Curtiss, Rajeev Thakur, Ian T. Foster
Colmena: Scalable Machine-Learning-Based Steering of Ensemble Simulations for High Performance Computing. MLHPC@SC (2021)
Jenna A. Bilbrey, Logan T. Ward, Sutanay Choudhury, Neeraj Kumar, Ganesh Sivaraman
Evening the Score: Targeting SARS-CoV-2 Protease Inhibition in Graph Generative Models for Therapeutic Candidates. CoRR (2021)
Zhi Hong, J. Gregory Pauloski, Logan T. Ward, Kyle Chard, Ben Blaiszik, Ian T. Foster
AI- and HPC-enabled Lead Generation for SARS-CoV-2: Models and Processes to Extract Druglike Molecules Contained in Natural Language Text. CoRR (2021)
Francis J. Alexander, James Ang, Jenna A. Bilbrey, Jan Balewski, Tiernan Casey, Ryan Chard, Jong Choi, Sutanay Choudhury, Bert J. Debusschere, Anthony M. DeGennaro, Nikoli Dryden, J. Austin Ellis, Ian T. Foster, Cristina Garcia-Cardona, Sayan Ghosh, Peter Harrington, Yunzhi Huang, Shantenu Jha, Travis Johnston, Ai Kagawa, Ramakrishnan Kannan, Neeraj Kumar, Zhengchun Liu, Naoya Maruyama, Satoshi Matsuoka, Erin McCarthy, Jamaludin Mohd-Yusof, Peter Nugent, Yosuke Oyama, Thomas Proffen, David Pugmire, Sivasankaran Rajamanickam, Vinay Ramakrishniah, Malachi Schram, Sudip K. Seal, Ganesh Sivaraman, Christine Sweeney, Li Tan, Rajeev Thakur, Brian Van Essen, Logan T. Ward, Paul M. Welch, Michael Wolf, Sotiris S. Xantheas, Kevin G. Yager, Shinjae Yoo, Byung-Jun Yoon
Co-design Center for Exascale Machine Learning Technologies (ExaLearn). Int. J. High Perform. Comput. Appl. 35 (6) (2021)
Logan T. Ward, Jenna A. Bilbrey, Sutanay Choudhury, Neeraj Kumar, Ganesh Sivaraman
Benchmarking Deep Graph Generative Models for Optimizing New Drug Molecules for COVID-19. CoRR (2021)
Thanh Son Phung, Logan T. Ward, Kyle Chard, Douglas Thain
Not All Tasks Are Created Equal: Adaptive Resource Allocation for Heterogeneous Tasks in Dynamic Workflows. WORKS (2021)
Logan T. Ward, Ganesh Sivaraman, J. Gregory Pauloski, Yadu N. Babuji, Ryan Chard, Naveen Dandu, Paul C. Redfern, Rajeev S. Assary, Kyle Chard, Larry A. Curtiss, Rajeev Thakur, Ian T. Foster
Colmena: Scalable Machine-Learning-Based Steering of Ensemble Simulations for High Performance Computing. CoRR (2021)
Zhuozhao Li, Ryan Chard, Logan T. Ward, Kyle Chard, Tyler J. Skluzacek, Yadu N. Babuji, Anna Woodard, Steven Tuecke, Ben Blaiszik, Michael J. Franklin, Ian T. Foster
DLHub: Simplifying publication, discovery, and use of machine learning models in science. J. Parallel Distributed Comput. 147 (2021)
Sutanay Choudhury, Jenna A. Bilbrey, Logan T. Ward, Sotiris S. Xantheas, Ian T. Foster, Joseph P. Heindel, Ben Blaiszik, Marcus E. Schwarting
HydroNet: Benchmark Tasks for Preserving Intermolecular Interactions and Structural Motifs in Predictive and Generative Models for Molecular Data. CoRR (2020)
Ryan Chard, Zhuozhao Li, Kyle Chard, Logan T. Ward, Yadu N. Babuji, Anna Woodard, Steven Tuecke, Ben Blaiszik, Michael J. Franklin, Ian T. Foster
DLHub: Model and Data Serving for Science. IPDPS (2019)
Ryan Chard, Logan T. Ward, Zhuozhao Li, Yadu N. Babuji, Anna Woodard, Steven Tuecke, Kyle Chard, Ben Blaiszik, Ian T. Foster
Publishing and Serving Machine Learning Models with DLHub. PEARC (2019)
Dipendra Jha, Logan T. Ward, Zijiang Yang, Christopher Wolverton, Ian T. Foster, Wei-keng Liao, Alok N. Choudhary, Ankit Agrawal
IRNet: A General Purpose Deep Residual Regression Framework for Materials Discovery. KDD (2019)
Tyler J. Skluzacek, Ryan Chard, Ryan Wong, Zhuozhao Li, Yadu N. Babuji, Logan T. Ward, Ben Blaiszik, Kyle Chard, Ian T. Foster
Serverless Workflows for Indexing Large Scientific Data. WOSC@Middleware (2019)
Roselyne Tchoua, Aswathy Ajith, Zhi Hong, Logan T. Ward, Kyle Chard, Debra Audus, Shrayesh Patel, Juan de Pablo, Ian T. Foster
Active Learning Yields Better Training Data for Scientific Named Entity Recognition. eScience (2019)
Dipendra Jha, Logan T. Ward, Zijiang Yang, Christopher Wolverton, Ian T. Foster, Wei-keng Liao, Alok N. Choudhary, Ankit Agrawal
IRNet: A General Purpose Deep Residual Regression Framework for Materials Discovery. CoRR (2019)
Roselyne B. Tchoua, Aswathy Ajith, Zhi Hong, Logan T. Ward, Kyle Chard, Alexander Belikov, Debra J. Audus, Shrayesh Patel, Juan J. de Pablo, Ian T. Foster
Creating Training Data for Scientific Named Entity Recognition with Minimal Human Effort. ICCS (1) (2019)
Matt Baughman, Ryan Chard, Logan T. Ward, Jason Pitt, Kyle Chard, Ian T. Foster
Profiling and Predicting Application Performance on the Cloud. UCC (2018)
Ryan Chard, Zhuozhao Li, Kyle Chard, Logan T. Ward, Yadu N. Babuji, Anna Woodard, Steven Tuecke, Ben Blaiszik, Michael J. Franklin, Ian T. Foster
DLHub: Model and Data Serving for Science. CoRR (2018)
Roselyne B. Tchoua, Kyle Chard, Debra J. Audus, Logan T. Ward, Joshua Lequieu, Juan J. de Pablo, Ian T. Foster
Towards a Hybrid Human-Computer Scientific Information Extraction Pipeline. eScience (2017)