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ORCIDJ. Gregory Pauloski
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2020 – today
- 2024
[c12]André Bauer, Maxime Gonthier, Haochen Pan, Ryan Chard, Daniel Grzenda, Martin Straesser, J. Gregory Pauloski, Alok Kamatar, Matt Baughman, Nathaniel Hudson, Ian T. Foster, Kyle Chard:
An Empirical Investigation of Container Building Strategies and Warm Times to Reduce Cold Starts in Scientific Computing Serverless Functions. e-Science 2024: 1-10- [c11]J. Gregory Pauloski, Valérie Hayot-Sasson, Maxime Gonthier, Nathaniel Hudson, Haochen Pan, Sicheng Zhou, Ian T. Foster, Kyle Chard:
TaPS: A Performance Evaluation Suite for Task-based Execution Frameworks. e-Science 2024: 1-10 - [i13]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) - [i12]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) - [i11]J. Gregory Pauloski, Valérie Hayot-Sasson, Maxime Gonthier, Nathaniel Hudson, Haochen Pan, Sicheng Zhou, Ian T. Foster, Kyle Chard:
TaPS: A Performance Evaluation Suite for Task-based Execution Frameworks. CoRR abs/2408.07236 (2024) - [i10]Logan T. Ward, J. Gregory Pauloski, Valérie Hayot-Sasson, Yadu N. Babuji, Alexander Brace, Ryan Chard, Kyle Chard, Rajeev Thakur, Ian T. Foster:
Employing Artificial Intelligence to Steer Exascale Workflows with Colmena. CoRR abs/2408.14434 (2024) - [i9]Nathaniel Hudson, Valérie Hayot-Sasson, Yadu N. Babuji, Matt Baughman, J. Gregory Pauloski, Ryan Chard, Ian T. Foster, Kyle Chard:
Flight: A FaaS-Based Framework for Complex and Hierarchical Federated Learning. CoRR abs/2409.16495 (2024) - 2023
- [j2]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) - [c10]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 - [c9]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 - [c8]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 - [c7]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 - [i8]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) - [i7]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) - [i6]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) - 2022
- [j1]J. Gregory Pauloski, Lei Huang, Weijia Xu, Kyle Chard, Ian T. Foster, Zhao Zhang:
Deep Neural Network Training With Distributed K-FAC. IEEE Trans. Parallel Distributed Syst. 33(12): 3616-3627 (2022) - [i5]Zhi Hong, Aswathy Ajith, J. Gregory Pauloski, Eamon Duede, Carl Malamud, Roger Magoulas, Kyle Chard, Ian T. Foster:
ScholarBERT: Bigger is Not Always Better. CoRR abs/2205.11342 (2022) - 2021
- [c6]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: 9-20 - [c5]J. Gregory Pauloski, Qi Huang, Lei Huang, Shivaram Venkataraman, Kyle Chard, Ian T. Foster, Zhao Zhang:
KAISA: an adaptive second-order optimizer framework for deep neural networks. SC 2021: 13 - [i4]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 abs/2101.04617 (2021) - [i3]J. Gregory Pauloski, Qi Huang, Lei Huang, Shivaram Venkataraman, Kyle Chard, Ian T. Foster, Zhao Zhang:
KAISA: An Adaptive Second-order Optimizer Framework for Deep Neural Networks. CoRR abs/2107.01739 (2021) - [i2]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 abs/2110.02827 (2021) - 2020
- [c4]Zhao Zhang, Lei Huang, J. Gregory Pauloski, Ian T. Foster:
Efficient I/O for Neural Network Training with Compressed Data. IPDPS 2020: 409-418 - [c3]J. Gregory Pauloski, Zhao Zhang, Lei Huang, Weijia Xu, Ian T. Foster:
Convolutional neural network training with distributed K-FAC. SC 2020: 94 - [i1]J. Gregory Pauloski, Zhao Zhang, Lei Huang, Weijia Xu, Ian T. Foster:
Convolutional Neural Network Training with Distributed K-FAC. CoRR abs/2007.00784 (2020)
2010 – 2019
- 2019
- [c2]Zhao Zhang, Lei Huang, J. Gregory Pauloski, Ian T. Foster:
Aggregating Local Storage for Scalable Deep Learning I/O. DLS@SC 2019: 69-75 - 2018
- [c1]Evan D. H. Gates, J. Gregory Pauloski, Dawid Schellingerhout, David Fuentes:
Glioma Segmentation and a Simple Accurate Model for Overall Survival Prediction. BrainLes@MICCAI (2) 2018: 476-484
Coauthor Index
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last updated on 2024-10-17 21:28 CEST by the dblp team
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