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ORCIDIan T. Foster
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- affiliation: University of Chicago, IL, USA
- affiliation: Argonne National Laboratory, Lemont, IL, USA
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2020 – today
- 2025
[j184]Thomas Bouvier
, Bogdan Nicolae, Alexandru Costan, Tekin Bicer, Ian T. Foster, Gabriel Antoniu:
Efficient distributed continual learning for steering experiments in real-time. Future Gener. Comput. Syst. 162: 107438 (2025)- 2024
- [j183]Rafael Ferreira da Silva, Rosa M. Badia, Deborah Bard, Ian T. Foster, Shantenu Jha, Frédéric Suter:
Frontiers in Scientific Workflows: Pervasive Integration With High-Performance Computing. Computer 57(8): 36-44 (2024) - [j182]André Bauer, Haochen Pan, Ryan Chard, Yadu N. Babuji, Josh Bryan, Devesh Tiwari, Ian T. Foster, Kyle Chard:
The globus compute dataset: An open function-as-a-service dataset from the edge to the cloud. Future Gener. Comput. Syst. 153: 558-574 (2024) - [j181]Nathaniel Hudson, Hana Khamfroush, Matt Baughman, Daniel E. Lucani, Kyle Chard, Ian T. Foster:
QoS-aware edge AI placement and scheduling with multiple implementations in FaaS-based edge computing. Future Gener. Comput. Syst. 157: 250-263 (2024) - [j180]Thomas Prantl, Lukas Horn, Simon Engel, Lukas Iffländer, Lukas Beierlieb, Christian Krupitzer, André Bauer, Mansi Sakarvadia, Ian T. Foster, Samuel Kounev:
De Bello Homomorphico: Investigation of the extensibility of the OpenFHE library with basic mathematical functions by means of common approaches using the example of the CKKS cryptosystem. Int. J. Inf. Sec. 23(2): 1149-1169 (2024) - [j179]Michael Stenger, Robert Leppich, Ian T. Foster, Samuel Kounev, André Bauer:
Evaluation is key: a survey on evaluation measures for synthetic time series. J. Big Data 11(1): 66 (2024) - [j178]Andrew S. Lee, Sarah Elliott, Hassan Harb, Logan T. Ward, Ian T. Foster, Larry A. Curtiss, Rajeev S. Assary:
Emin: A First-Principles Thermochemical Descriptor for Predicting Molecular Synthesizability. J. Chem. Inf. Model. 64(4): 1277-1289 (2024) - [j177]Michael Stenger, André Bauer, Thomas Prantl, Robert Leppich, Nathaniel Hudson, Kyle Chard, Ian T. Foster, Samuel Kounev:
Thinking in Categories: A Survey on Assessing the Quality for Time Series Synthesis. ACM J. Data Inf. Qual. 16(2): 14:1-14:32 (2024) - [j176]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 T. Foster, Ben Blaiszik:
Foundry-ML - Software and Services to Simplify Access to Machine Learning Datasets in Materials Science. J. Open Source Softw. 9(93): 5467 (2024) - [c446]Maksim Levental, Arham Khan, Ryan Chard, Kazutomo Yoshii, Kyle Chard, Ian T. Foster:
BraggHLS: High-Level Synthesis for Low-Latency Deep Neural Networks for Experimental Science. HEART 2024: 10-17 - [c445]Maksim Levental, Arham Khan, Ryan Chard, Kyle Chard, Stephen Neuendorffer, Ian T. Foster:
An End-to-End Programming Model for AI Engine Architectures. HEART 2024: 135-136 - [c444]Yifei Li, Ryan Chard, Yadu N. Babuji, Kyle Chard, Ian T. Foster, Zhuozhao Li:
UniFaaS: Programming across Distributed Cyberinfrastructure with Federated Function Serving. IPDPS 2024: 217-229 - [c443]Alok Kamatar, Valérie Hayot-Sasson, Yadu N. Babuji, André Bauer, Gourav Rattihalli, Ninad Hogade, Dejan S. Milojicic, Kyle Chard, Ian T. Foster:
Enhancing Energy Efficiency with Multi-Site Scheduling Strategies. IPDPS (Workshops) 2024: 1175-1177 - [c442]André Bauer, Timo Dittus, Martin Straesser, Alok Kamatar, Matt Baughman, Lukas Beierlieb, Marius Hadry, Daniel Grillmeyer, Yannik Lubas, Samuel Kounev, Ian T. Foster, Kyle Chard:
Unveiling Temporal Performance Deviation: Leveraging Clustering in Microservices Performance Analysis. ICPE (Companion) 2024: 72-76 - [c441]Xiaolong Ma, Feng Yan, Lei Yang, Ian T. Foster, Michael E. Papka, Zhengchun Liu, Rajkumar Kettimuthu:
MalleTrain: Deep Neural Networks Training on Unfillable Supercomputer Nodes. ICPE 2024: 190-200 - [c440]Joe Bottigliero, Rachana Ananthakrishnan, Kyle Chard, Ryan Chard, Ian T. Foster:
Zero Code and Infrastructure Research Data Portals. PEARC 2024: 36:1-36:4 - [c439]Rachana Ananthakrishnan, Yadu N. Babuji, Matt Baughman, Josh Bryan, Kyle Chard, Ryan Chard, Ben Clifford, Ian T. Foster, Daniel S. Katz, Kevin Hunter Kesling, Chris Janidlo, Reid Mello, Lei Wang:
Enabling Remote Management of FaaS Endpoints with Globus Compute Multi-User Endpoints. PEARC 2024: 62:1-62:5 - [d5]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 Ferris, Paul M. Voyles, Dane Morgan, Ian T. Foster, Ben Blaiszik:
Foundry-ML (latest). Zenodo, 2024
- [d4]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 Ferris, Paul M. Voyles, Dane Morgan, Ian T. Foster, Ben Blaiszik:
Foundry-ML - Software and Services to Simplify Access to Machine Learning Datasets in Materials Science. Version v0.5.0. Zenodo, 2024 [all versions] - [d3]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 Ferris, Paul M. Voyles, Dane Morgan, Ian T. Foster, Ben Blaiszik:
Foundry-ML - Software and Services to Simplify Access to Machine Learning Datasets in Materials Science. Version 2. Zenodo, 2024 [all versions] - [d2]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 Ferris, Paul M. Voyles, Dane Morgan, Ian T. Foster, Ben Blaiszik:
Foundry-ML - Software and Services to Simplify Access to Machine Learning Datasets in Materials Science. Version v0.7.4. Zenodo, 2024 [all versions] - [i133]André Bauer, Simon Trapp, Michael Stenger, Robert Leppich, Samuel Kounev, Mark Leznik, Kyle Chard, Ian T. Foster:
Comprehensive Exploration of Synthetic Data Generation: A Survey. CoRR abs/2401.02524 (2024) - [i132]Torsten Hoefler, Marcin Copik, Pete Beckman, Andrew Jones, Ian T. Foster, Manish Parashar, Daniel A. Reed, Matthias Troyer, Thomas C. Schulthess, Dan Ernst, Jack J. Dongarra:
XaaS: Acceleration as a Service to Enable Productive High-Performance Cloud Computing. CoRR abs/2401.04552 (2024) - [i131]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 abs/2402.03480 (2024) - [i130]Zhi Hong, Kyle Chard, Ian T. Foster:
Combining Language and Graph Models for Semi-structured Information Extraction on the Web. CoRR abs/2402.14129 (2024) - [i129]Jim Pruyne, Valérie Hayot-Sasson, Weijian Zheng, Ryan Chard, Justin M. Wozniak, Tekin Bicer, Kyle Chard, Ian T. Foster:
Steering a Fleet: Adaptation for Large-Scale, Workflow-Based Experiments. CoRR abs/2403.06077 (2024) - [i128]Yifei Li, Ryan Chard, Yadu N. Babuji, Kyle Chard, Ian T. Foster, Zhuozhao Li:
UniFaaS: Programming across Distributed Cyberinfrastructure with Federated Function Serving. CoRR abs/2403.19257 (2024) - [i127]Yuanjian Liu, Huihao Luo, Zhijun Han, Yao Hu, Yehui Yang, Kyle Chard, Sheng Di, Ian T. Foster, Jiesheng Wu:
FastqZip: An Improved Reference-Based Genome Sequence Lossy Compression Framework. CoRR abs/2404.02163 (2024) - [i126]Marcus Schwarting, Nathan A. Seifert, Michael J. Davis, Ben Blaiszik, Ian T. Foster, Kirill Prozument:
Twins in rotational spectroscopy: Does a rotational spectrum uniquely identify a molecule? CoRR abs/2404.04225 (2024) - [i125]Xiaolong Ma, Feng Yan, Lei Yang, Ian T. Foster, Michael E. Papka, Zhengchun Liu, Rajkumar Kettimuthu:
MalleTrain: Deep Neural Network Training on Unfillable Supercomputer Nodes. CoRR abs/2404.15668 (2024) - [i124]Lukasz Lacinski, Lee Liming, Steven Turoscy, Cameron Harr, Kyle Chard, Eli Dart, Paul Durack, Sasha Ames, Forrest M. Hoffman, Ian T. Foster:
Automated, Reliable, and Efficient Continental-Scale Replication of 7.3 Petabytes of Climate Simulation Data: A Case Study. CoRR abs/2404.19717 (2024) - [i123]Yuwei Wan, Aswathy Ajith, Yixuan Liu, Ke Lu, Clara Grazian, Bram Hoex, Wenjie Zhang, Chunyu Kit, Tong Xie, Ian T. Foster:
SciQAG: A Framework for Auto-Generated Scientific Question Answering Dataset with Fine-grained Evaluation. CoRR abs/2405.09939 (2024) - [i122]Eamon Duede, William B. Dolan, André Bauer, Ian T. Foster, Karim R. Lakhani:
Oil & Water? Diffusion of AI Within and Across Scientific Fields. CoRR abs/2405.15828 (2024) - [i121]Thomas Bouvier, Bogdan Nicolae, Hugo Chaugier, Alexandru Costan, Ian T. Foster, Gabriel Antoniu:
Efficient Data-Parallel Continual Learning with Asynchronous Distributed Rehearsal Buffers. CoRR abs/2406.03285 (2024) - [i120]Ashka Shah, Adela DePavia, Nathaniel Hudson, Ian T. Foster, Rick Stevens:
Causal Discovery over High-Dimensional Structured Hypothesis Spaces with Causal Graph Partitioning. CoRR abs/2406.06348 (2024) - [i119]Alok Kamatar, Valérie Hayot-Sasson, Yadu N. Babuji, André Bauer, Gourav Rattihalli, Ninad Hogade, Dejan S. Milojicic, Kyle Chard, Ian T. Foster:
GreenFaaS: Maximizing Energy Efficiency of HPC Workloads with FaaS. CoRR abs/2406.17710 (2024) - [i118]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 abs/2407.01764 (2024) - 2023
- [j175]Samuel Kounev, Nikolas Herbst, Cristina L. Abad, Alexandru Iosup, Ian T. Foster, Prashant J. Shenoy, Omer F. Rana, Andrew A. Chien:
Serverless Computing: What It Is, and What It Is Not? Commun. ACM 66(9): 80-92 (2023) - [j174]Ryan Chard, Jim Pruyne, Kurt McKee, Josh Bryan, Brigitte Raumann, Rachana Ananthakrishnan, Kyle Chard, Ian T. Foster:
Globus automation services: Research process automation across the space-time continuum. Future Gener. Comput. Syst. 142: 393-409 (2023) - [j173]Maxim Zvyagin, Alexander Brace, Kyle Hippe, Yuntian Deng, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael W. Irvin, Defne G. Ozgulbas, Natalia Vassilieva, J. Gregory Pauloski, Logan T. Ward, Valérie Hayot-Sasson, Murali Emani, Sam Foreman, Zhen Xie, Diangen Lin, Maulik Shukla, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Ian T. Foster, James J. Davis, Michael E. Papka, Thomas S. Brettin, Rick Stevens, Anima Anandkumar, Venkatram Vishwanath, Arvind Ramanathan:
GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics. Int. J. High Perform. Comput. Appl. 37(6): 683-705 (2023) - [j172]Melanie Po-Leen Ooi, Shaleeza Sohail, Victoria Guiying Huang, Nathaniel Hudson, Matt Baughman, Omer F. Rana, Annika Hinze, Kyle Chard, Ryan Chard, Ian T. Foster, Theodoros Spyridopoulos, Harshaan Nagra:
Measurement and Applications: Exploring the Challenges and Opportunities of Hierarchical Federated Learning in Sensor Applications. IEEE Instrum. Meas. Mag. 26(9): 21-31 (2023) - [j171]Rosa M. Badia, Ian T. Foster, Dejan S. Milojicic:
Future of HPC. IEEE Internet Comput. 27(1): 5-6 (2023) - [j170]Panos Patros, Melanie Ooi, Victoria Huang, Michael Mayo, Chris Anderson, Stephen Burroughs, Matt Baughman, Osama Almurshed, Omer F. Rana, Ryan Chard, Kyle Chard, Ian T. Foster:
Rural AI: Serverless-Powered Federated Learning for Remote Applications. IEEE Internet Comput. 27(2): 28-34 (2023) - [c438]Zhi Hong, Aswathy Ajith, J. Gregory Pauloski, Eamon Duede, Kyle Chard, Ian T. Foster:
The Diminishing Returns of Masked Language Models to Science. ACL (Findings) 2023: 1270-1283 - [c437]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: 15:1-15:10 - [c436]Mansi Sakarvadia, Aswathy Ajith, Arham Khan, Daniel Grzenda, Nathaniel Hudson, André Bauer, Kyle Chard, Ian T. Foster:
Memory Injections: Correcting Multi-Hop Reasoning Failures During Inference in Transformer-Based Language Models. BlackboxNLP@EMNLP 2023: 342-356 - [c435]Martin Straesser, André Bauer, Robert Leppich, Nikolas Herbst, Kyle Chard, Ian T. Foster, Samuel Kounev:
An Empirical Study of Container Image Configurations and Their Impact on Start Times. CCGrid 2023: 94-105 - [c434]Zhengchun Liu, Rajkumar Kettimuthu, Michael E. Papka, Ian T. Foster:
FreeTrain: A Framework to Utilize Unused Supercomputer Nodes for Training Neural Networks. CCGrid 2023: 299-310 - [c433]Arham Khan, Sheng Di, Kai Zhao, Jinyang Liu, Kyle Chard, Ian T. Foster, Franck Cappello:
An Efficient and Accurate Compression Ratio Estimation Model for SZx. CLUSTER Workshops 2023: 48-49 - [c432]Mihael Hategan-Marandiuc, André Merzky, Nicholson T. Collier, Ketan Maheshwari, Jonathan Ozik, Matteo Turilli, Andreas Wilke, Justin M. Wozniak, Kyle Chard, Ian T. Foster, Rafael Ferreira da Silva, Shantenu Jha, Daniel E. Laney:
PSI/J: A Portable Interface for Submitting, Monitoring, and Managing Jobs. e-Science 2023: 1-10 - [c431]Alok Kamatar, Mansi Sakarvadia, Valérie Hayot-Sasson, Kyle Chard, Ian T. Foster:
Lazy Python Dependency Management in Large-Scale Systems. e-Science 2023: 1-10 - [c430]Carl Kesselman, Robert Schuler, Ian T. Foster:
Let's Put the Science in eScience. e-Science 2023: 1-3 - [c429]Tyler J. Skluzacek, Kyle Chard, Ian T. Foster:
Can Automated Metadata Extraction Make Scientific Data More Navigable? e-Science 2023: 1-10 - [c428]Aniket Tekawade, Viktor V. Nikitin, Yashas Satapathy, Zhengchun Liu, Xuan Zhang, Peter Kenesei, Weijian Zheng, Francesco De Carlo, Ian T. Foster, Rajkumar Kettimuthu:
Tomo2Mesh: Fast Porosity Mapping and Visualization for Synchrotron Tomography. e-Science 2023: 1-10 - [c427]Arham Khan, Sheng Di, Kai Zhao, Jinyang Liu, Kyle Chard, Ian T. Foster, Franck Cappello:
SECRE: Surrogate-Based Error-Controlled Lossy Compression Ratio Estimation Framework. HiPC 2023: 132-142 - [c426]Lipeng Wan, Jieyang Chen, Xin Liang, Ana Gainaru, Qian Gong, Qing Liu, Ben Whitney, Joy Arulraj, Zhengchun Liu, Ian T. Foster, Scott Klasky:
RAPIDS: Reconciling Availability, Accuracy, and Performance in Managing Geo-Distributed Scientific Data. HPDC 2023: 87-100 - [c425]Yuanjian Liu, Sheng Di, Kyle Chard, Ian T. Foster, Franck Cappello:
Optimizing Scientific Data Transfer on Globus with Error-Bounded Lossy Compression. ICDCS 2023: 703-713 - [c424]Aswathy Ajith, Marcus Schwarting, Zhi Hong, Kyle Chard, Ian T. Foster:
MatPropXtractor: Generate to Extract. Tiny Papers @ ICLR 2023 - [c423]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: 32-41 - [c422]Maurice Weber, Carlo Siebenschuh, Rory Butler, Anton Alexandrov, Valdemar Thanner, Georgios Tsolakis, Haris Jabbar, Ian T. Foster, Bo Li, Rick Stevens, Ce Zhang:
WordScape: a Pipeline to extract multilingual, visually rich Documents with Layout Annotations from Web Crawl Data. NeurIPS 2023 - [c421]Matt Baughman, Nathaniel Hudson, Ian T. Foster, Kyle Chard:
Balancing Federated Learning Trade-Offs for Heterogeneous Environments. PerCom Workshops 2023: 404-407 - [c420]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: 59:1-59:15 - [c419]Matt Baughman, Nathaniel Hudson, Ryan Chard, André Bauer, Ian T. Foster, Kyle Chard:
Tournament-Based Pretraining to Accelerate Federated Learning. SC Workshops 2023: 109-115 - [c418]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: 1606-1613 - [c417]Alexander Brace, Rafael Vescovi, Ryan Chard, Nickolaus D. Saint, Arvind Ramanathan, Nestor J. Zaluzec, Ian T. Foster:
Linking the Dynamic PicoProbe Analytical Electron-Optical Beam Line / Microscope to Supercomputers. SC Workshops 2023: 2140-2146 - [c416]Tobias Ginsburg, Kyle Hippe, Ryan Lewis, Aileen Cleary, Doga Ozgulbas, Rory Butler, Casey Stone, Abraham Stroka, Rafael Vescovi, Ian T. Foster:
Exploring Benchmarks for Self-Driving Labs using Color Matching. SC Workshops 2023: 2147-2152 - [c415]André Bauer, Martin Straesser, Mark Leznik, Lukas Beierlieb, Marius Hadry, Nathaniel Hudson, Kyle Chard, Samuel Kounev, Ian T. Foster:
Searching for the Ground Truth: Assessing the Similarity of Benchmarking Runs. ICPE (Companion) 2023: 95-99 - [c414]Nickolaus D. Saint, Ryan Chard, Rafael Vescovi, Jim Pruyne, Ben Blaiszik, Rachana Ananthakrishnan, Michael E. Papka, Rick Wagner, Kyle Chard, Ian T. Foster:
Active Research Data Management with the Django Globus Portal Framework. PEARC 2023: 43-51 - [c413]Rachana Ananthakrishnan, Josh Bryan, Kyle Chard, Ryan Chard, Kurt McKee, Ada Nikolaidis, Jim Pruyne, Stephen Rosen, Ian T. Foster:
Globus Timers: Scheduling Periodic Data Management Actions on Distributed Research Infrastructure. PEARC 2023: 283-287 - [d1]Martin Straesser, André Bauer, Robert Leppich, Nikolas Herbst, Kyle Chard, Ian T. Foster, Samuel Kounev:
An Empirical Study of Container Image Configurations and Their Impact on Start Times (Container Image Data). Zenodo, 2023 - [i117]Maksim Levental, Arham Khan, Ryan Chard, Kazutomo Yoshii, Kyle Chard, Ian T. Foster:
OpenHLS: High-Level Synthesis for Low-Latency Deep Neural Networks for Experimental Science. CoRR abs/2302.06751 (2023) - [i116]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 abs/2303.08803 (2023) - [i115]Omer F. Rana, Theodoros Spyridopoulos, Nathaniel Hudson, Matt Baughman, Kyle Chard, Ian T. Foster, Aftab Khan:
Hierarchical and Decentralised Federated Learning. CoRR abs/2304.14982 (2023) - [i114]Siyuan Xia, Zhiru Zhu, Chris Zhu, Jinjin Zhao, Kyle Chard, Aaron J. Elmore, Ian T. Foster, Michael J. Franklin, Sanjay Krishnan, Raul Castro Fernandez:
Data Station: Delegated, Trustworthy, and Auditable Computation to Enable Data-Sharing Consortia with a Data Escrow. CoRR abs/2305.03842 (2023) - [i113]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 abs/2305.09593 (2023) - [i112]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 abs/2306.06283 (2023) - [i111]Hyun Park, Xiaoli Yan, Ruijie Zhu, Eliu A. Huerta, Santanu Chaudhuri, Donny Cooper, Ian T. Foster, Emad Tajkhorshid:
GHP-MOFassemble: Diffusion modeling, high throughput screening, and molecular dynamics for rational discovery of novel metal-organic frameworks for carbon capture at scale. CoRR abs/2306.08695 (2023) - [i110]Yuanjian Liu, Sheng Di, Kyle Chard, Ian T. Foster, Franck Cappello:
Optimizing Scientific Data Transfer on Globus with Error-bounded Lossy Compression. CoRR abs/2307.05416 (2023) - [i109]Mihael Hategan-Marandiuc, André Merzky, Nicholson T. Collier, Ketan Maheshwari, Jonathan Ozik, Matteo Turilli, Andreas Wilke, Justin M. Wozniak, Kyle Chard, Ian T. Foster, Rafael Ferreira da Silva, Shantenu Jha, Daniel E. Laney:
PSI/J: A Portable Interface for Submitting, Monitoring, and Managing Jobs. CoRR abs/2307.07895 (2023) - [i108]Maksim Levental, Alok Kamatar, Ryan Chard, Nicolas Vasilache, Kyle Chard, Ian T. Foster:
nelli: a lightweight frontend for MLIR. CoRR abs/2307.16080 (2023) - [i107]Rafael Vescovi, Tobias Ginsburg, Kyle Hippe, Doga Ozgulbas, Casey Stone, Abraham Stroka, Rory Butler, Ben Blaiszik, Tom Brettin, Kyle Chard, Mark Hereld, Arvind Ramanathan, Rick Stevens, Aikaterini Vriza, Jie Xu, Qingteng Zhang, Ian T. Foster:
Towards a Modular Architecture for Science Factories. CoRR abs/2308.09793 (2023) - [i106]Alexander Brace, Rafael Vescovi, Ryan Chard, Nickolaus D. Saint, Arvind Ramanathan, Nestor J. Zaluzec, Ian T. Foster:
Linking the Dynamic PicoProbe Analytical Electron-Optical Beam Line / Microscope to Supercomputers. CoRR abs/2308.13701 (2023) - [i105]Mansi Sakarvadia, Aswathy Ajith, Arham Khan, Daniel Grzenda, Nathaniel Hudson, André Bauer, Kyle Chard, Ian T. Foster:
Memory Injections: Correcting Multi-Hop Reasoning Failures during Inference in Transformer-Based Language Models. CoRR abs/2309.05605 (2023) - [i104]André Bauer, Mark Leznik, Michael Stenger, Robert Leppich, Nikolas Herbst, Samuel Kounev, Ian T. Foster:
Telescope: An Automated Hybrid Forecasting Approach on a Level-Playing Field. CoRR abs/2309.15871 (2023) - [i103]Tobias Ginsburg, Kyle Hippe, Ryan Lewis, Doga Ozgulbas, Aileen Cleary, Rory Butler, Casey Stone, Abraham Stroka, Ian T. Foster:
Exploring Benchmarks for Self-Driving Labs using Color Matching. CoRR abs/2310.00510 (2023) - [i102]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) - [i101]Mansi Sakarvadia, Arham Khan, Aswathy Ajith, Daniel Grzenda, Nathaniel Hudson, André Bauer, Kyle Chard, Ian T. Foster:
Attention Lens: A Tool for Mechanistically Interpreting the Attention Head Information Retrieval Mechanism. CoRR abs/2310.16270 (2023) - [i100]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 abs/2311.00787 (2023) - [i99]Tung Nguyen, Rohan Shah, Hritik Bansal, Troy Arcomano, Sandeep Madireddy, Romit Maulik, Veerabhadra Kotamarthi, Ian T. Foster, Aditya Grover:
Scaling transformer neural networks for skillful and reliable medium-range weather forecasting. CoRR abs/2312.03876 (2023) - [i98]Weijian Zheng, Jun-Sang Park, Peter Kenesei, Ahsan Ali, Zhengchun Liu, Ian T. Foster, Nicholas Schwarz, Rajkumar Kettimuthu, Antonino Miceli, Hemant Sharma:
Rapid detection of rare events from in situ X-ray diffraction data using machine learning. CoRR abs/2312.03989 (2023) - [i97]Maurice Weber, Carlo Siebenschuh, Rory Butler, Anton Alexandrov, Valdemar Thanner, Georgios Tsolakis, Haris Jabbar, Ian T. Foster, Bo Li, Rick Stevens, Ce Zhang:
WordScape: a Pipeline to extract multilingual, visually rich Documents with Layout Annotations from Web Crawl Data. CoRR abs/2312.10188 (2023) - 2022
- [j169]Rosa M. Badia, Ian T. Foster, Dejan S. Milojicic:
More Real Than Real: The Race to Simulate Everything. Computer 55(7): 67-72 (2022) - [j168]Ian T. Foster, Carl Kesselman:
CUF-Links: Continuous and Ubiquitous FAIRness Linkages for Reproducible Research. Computer 55(8): 20-30 (2022) - [j167]Kshitij Mehta, Bryce Allen, Matthew Wolf, Jeremy Logan, Eric Suchyta, Swati Singhal, Jong Youl Choi, Keichi Takahashi, Kevin A. Huck, Igor Yakushin, Alan Sussman, Todd S. Munson, Ian T. Foster, Scott Klasky:
A codesign framework for online data analysis and reduction. Concurr. Comput. Pract. Exp. 34(14) (2022) - [j166]