Sam Foreman

According to our database, Sam Foreman authored at least 15 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2025

AERIS: Argonne Earth Systems Model for Reliable and Skillful Predictions.

Väinö Hatanpää, Eugene Ku, Jason Stock, Murali Emani, Sam Foreman, Chunyong Jung, Sandeep Madireddy, Tung Nguyen, Varuni Katti Sastry, Ray A. O. Sinurat, Sam Wheeler, Huihuo Zheng, Troy Arcomano, Venkatram Vishwanath, Rao Kotamarthi

CoRR, September, 2025

Aurora: Architecting Argonne's First Exascale Supercomputer for Accelerated Scientific Discovery.

Benjamin S. Allen, James L. Anchell, Victor Anisimov, Thomas Applencourt, Abhishek Bagusetty, Ramesh Balakrishnan, Riccardo Balin, Solomon Bekele, Colleen Bertoni, Cyrus Blackworth, Renzo Bustamante, Kevin Canada, John Carrier, Christopher Chan-nui, Lance C. Cheney, J. Taylor Childers, Paul K. Coffman, Susan Coghlan, Michael D'Mello, Murali Emani, Kyle Felker, Sam Foreman, Olivier Franza, Longfei Gao, Marta García, María Jesús Garzarán, Balazs Gerofi, Yasaman Ghadar, Neha Gupta, Kevin Harms, Väinö Hatanpää, Brian Holland, Carissa Holohan, Brian Homerding, Khalid Hossain, Louise Huot, Huda Ibeid, Joseph A. Insley, Sai Jayanthi, Hong Jiang, Wei Jiang, Xiao-Yong Jin, Jeongnim Kim, Christopher Knight, Kalyan Kumaran, JaeHyuk Kwack, Ti Leggett, Ben Lenard, Chris Lewis, Nevin Liber, Johann Lombardi, Raymond M. Loy, Ye Luo, Bethany Lusch, Nilakantan Mahadevan, Victor A. Mateevitsi, Gordon McPheeters, Ryan Milner, Vitali A. Morozov, Servesh Muralidharan, Tom Musta, Mrigendra Nagar, Vikram Narayana, Marieme Ngom, Anthony-Trung Nguyen, Nathan Nichols, Aditya Nishtala, James C. Osborn, Michael E. Papka, Scott Parker, Saumil Patel, Adrian C. Pope, Sucheta Raghunanda, Esteban Rangel, Paul M. Rich, Silvio Rizzi, Kris Rowe, Varuni Sastry, Adam Scovel, Filippo Simini, Haritha Siddabathuni Som, Patrick Steinbrecher, Rick Stevens, Xinmin Tian, Peter Upton, Thomas D. Uram, Archit Vasan, Álvaro Vázquez-Mayagoitia, Kaushik Velusamy, Brice Videau, Venkatram Vishwanath, Brian Whitney, Timothy J. Williams, Michael Woodacre, Sam Zeltner, Gengbin Zheng, Huihuo Zheng

CoRR, September, 2025

HiPerRAG: High-Performance Retrieval Augmented Generation for Scientific Insights.

Ozan Gökdemir, Carlo Siebenschuh, Alexander Brace, Azton Wells, Brian Hsu, Kyle Hippe, Priyanka Vasanthakumari, Aswathy Ajith, J. Gregory Pauloski, Varuni Katti Sastry, Sam Foreman, Huihuo Zheng, Heng Ma, Bharat Kale, Nicholas Chia, Thomas Gibbs, Michael E. Papka, Thomas S. Brettin, Francis J. Alexander, Anima Anandkumar, Ian T. Foster, Rick Stevens, Venkatram Vishwanath, Arvind Ramanathan

CoRR, May, 2025

MOFA: Discovering Materials for Carbon Capture with a GenAI- and Simulation-Based Workflow.

Xiaoli Yan, Nathaniel Hudson, Hyun Park, Daniel Grzenda, J. Gregory Pauloski, Marcus Schwarting, Haochen Pan, Hassan Harb, Sam Foreman, Chris Knight, Tom Gibbs, Kyle Chard, Santanu Chaudhuri, Emad Tajkhorshid, Ian T. Foster, Mohamad Moosavi, Logan T. Ward, Eliu A. Huerta

CoRR, January, 2025

HiPerRAG: High-Performance Retrieval Augmented Generation for Scientific Insights.

Ozan Gökdemir, Carlo Siebenschuh, Alexander Brace, Azton Wells, Brian Hsu, Kyle Hippe, Priyanka Setty, Aswathy Ajith, J. Gregory Pauloski, Varuni Sastry, Sam Foreman, Huihuo Zheng, Heng Ma, Bharat Kale, Nicholas Chia, Thomas Gibbs, Michael E. Papka, Thomas S. Brettin, Francis J. Alexander, Anima Anandkumar, Ian T. Foster, Rick Stevens, Venkatram Vishwanath, Arvind Ramanathan

Proceedings of the Platform for Advanced Scientific Computing Conference, 2025

2024

Thorough Characterization and Analysis of Large Transformer Model Training At-Scale.

Scott Cheng, Jun-Liang Lin, Murali Emani, Siddhisanket Raskar, Sam Foreman, Zhen Xie, Venkatram Vishwanath, Mahmut T. Kandemir

Proceedings of the Abstracts of the 2024 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems, 2024

MProt-DPO: Breaking the ExaFLOPS Barrier for Multimodal Protein Design Workflows with Direct Preference Optimization.

Gautham Dharuman, Kyle Hippe, Alexander Brace, Sam Foreman, Väinö Hatanpää, Varuni Katti Sastry, Huihuo Zheng, Logan T. Ward, Servesh Muralidharan, Archit Vasan, Bharat Kale, Carla M. Mann, Heng Ma, Yun-Hsuan Cheng, Yuliana Zamora, Shengchao Liu, Chaowei Xiao, Murali Emani, Tom Gibbs, Mahidhar Tatineni, Deepak Canchi, Jerome Mitchell, Koichi Yamada, Maria Garzaran, Michael E. Papka, Ian T. Foster, Rick Stevens, Anima Anandkumar, Venkatram Vishwanath, Arvind Ramanathan

Proceedings of the International Conference for High Performance Computing, 2024

Toward a Holistic Performance Evaluation of Large Language Models Across Diverse AI Accelerators.

Murali Emani, Sam Foreman, Varuni Sastry, Zhen Xie, Siddhisanket Raskar, William Arnold, Rajeev Thakur, Venkatram Vishwanath, Michael E. Papka, Sanjif Shanmugavelu, Darshan Gandhi, Hengyu Zhao, Dun Ma, Kiran Ranganath, Rick Weisner, Jiunn-Yeu Chen, Yuting Yang, Natalia Vassilieva, Bin C. Zhang, Sylvia Howland, Alexander Tsyplikhin

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

2023

GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics.

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

Int. J. High Perform. Comput. Appl., November, 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 W. Schulz, Yuntian Deng, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Anima Anandkumar, Rick Stevens

CoRR, 2023

A Comprehensive Performance Study of Large Language Models on Novel AI Accelerators.

Murali Emani, Sam Foreman, Varuni Sastry, Zhen Xie, Siddhisanket Raskar, William Arnold, Rajeev Thakur, Venkatram Vishwanath, Michael E. Papka

CoRR, 2023

2022

Applications of Machine Learning to Lattice Quantum Field Theory.

Denis Boyda, Salvatore Calì, Sam Foreman, Lena Funcke, Daniel C. Hackett, Yin Lin, Gert Aarts, Andrei Alexandru, Xiao-Yong Jin, Biagio Lucini, Phiala E. Shanahan

CoRR, 2022

2021

HMC with Normalizing Flows.

Sam Foreman, Taku Izubuchi, Luchang Jin, Xiao-Yong Jin, James C. Osborn, Akio Tomiya

CoRR, 2021

LeapfrogLayers: A Trainable Framework for Effective Topological Sampling.

Sam Foreman, Xiao-Yong Jin, James C. Osborn

CoRR, 2021

Deep Learning Hamiltonian Monte Carlo.

Sam Foreman, Xiao-Yong Jin, James C. Osborn

CoRR, 2021