Tom Gibbs

According to our database, Tom Gibbs authored at least 15 papers between 2019 and 2023.

Collaborative distances:

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

2023

AI-Augmented Facilities: Bridging Experiment and Simulation with ML (Dagstuhl Seminar 23132).

Peer-Timo Bremer, Brian K. Spears, Tom Gibbs, Michael Bussmann

Dagstuhl Reports, March, 2023

#COVIDisAirborne: AI-enabled multiscale computational microscopy of delta SARS-CoV-2 in a respiratory aerosol.

Abigail C. Dommer, Lorenzo Casalino, Fiona L. Kearns, Mia Rosenfeld, Nicholas Wauer, Surl-Hee Ahn, John Russo, A. Sofia F. Oliveira, Clare Morris, Anthony T. Bogetti, Anda Trifan, Alexander Brace, Terra Sztain, Austin Clyde, Heng Ma, S. Chakra Chennubhotla, Hyungro Lee, Matteo Turilli, Syma Khalid, Teresa Tamayo-Mendoza, Matthew Welborn, Anders S. Christensen, Daniel G. A. Smith, Zhuoran Qiao, Sai K. Sirumalla, Michael O'Connor, Frederick R. Manby, Anima Anandkumar, David J. Hardy, James C. Phillips, Abraham C. Stern, Josh Romero, David Clark, Mitchell Dorrell, Tom Maiden, Lei Huang, John D. McCalpin, Christopher J. Woods, Alan Gray, Matt Williams, Bryan Barker, Harinda Rajapaksha, Richard Pitts, Tom Gibbs, John E. Stone, Daniel M. Zuckerman, Adrian J. Mulholland, Thomas F. Miller III, Shantenu Jha, Arvind Ramanathan, Lillian T. Chong, Rommie E. Amaro

Int. J. High Perform. Comput. Appl., 2023

2022

ProtTrans: Toward Understanding the Language of Life Through Self-Supervised Learning.

Ahmed Elnaggar, Michael Heinzinger, Christian Dallago, Ghalia Rehawi, Yu Wang, Llion Jones, Tom Gibbs, Tamas Feher, Christoph Angerer, Martin Steinegger, Debsindhu Bhowmik, Burkhard Rost

IEEE Trans. Pattern Anal. Mach. Intell., 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

Accelerating IceCube's Photon Propagation Code with CUDA.

Hendrik Schwanekamp, Ramona Hohl, Dmitry Chirkin, Tom Gibbs, Alexander Harnisch, Claudio Kopper, Peter Messmer, Vishal Mehta, Alexander R. Olivas, Benedikt Riedel, Martin Rongen, David Schultz, Jakob van Santen

Comput. Softw. Big Sci., 2022

Performance Evaluation and Acceleration of the QTensor Quantum Circuit Simulator on GPUs.

Danylo Lykov, Angela Chen, Huaxuan Chen, Kristopher Keipert, Zheng Zhang, Tom Gibbs, Yuri Alexeev

CoRR, 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

2021

AI-driven multiscale simulations illuminate mechanisms of SARS-CoV-2 spike dynamics.

Lorenzo Casalino, Abigail C. Dommer, Zied Gaieb, Emília P. Barros, Terra Sztain, Surl-Hee Ahn, Anda Trifan, Alexander Brace, Anthony T. Bogetti, Austin Clyde, Heng Ma, Hyungro Lee, Matteo Turilli, Syma Khalid, Lillian T. Chong, Carlos Simmerling, David J. Hardy, Julio D. C. Maia, James C. Phillips, Thorsten Kurth, Abraham C. Stern, Lei Huang, John D. McCalpin, Mahidhar Tatineni, Tom Gibbs, John E. Stone, Shantenu Jha, Arvind Ramanathan, Rommie E. Amaro

Int. J. High Perform. Comput. Appl., 2021

CodeTrans: Towards Cracking the Language of Silicone's Code Through Self-Supervised Deep Learning and High Performance Computing.

Ahmed Elnaggar, Wei Ding, Llion Jones, Tom Gibbs, Tamas Feher, Christoph Angerer, Silvia Severini, Florian Matthes, Burkhard Rost

CoRR, 2021

NVIDIA's Cloud Native Supercomputing.

Gilad Shainer, Richard L. Graham, Chris J. Newburn, Oscar R. Hernandez, Gil Bloch, Tom Gibbs, Jack C. Wells

Proceedings of the Driving Scientific and Engineering Discoveries Through the Integration of Experiment, Big Data, and Modeling and Simulation, 2021

Enabling ISO Standard Languages for Complex HPC Workflows.

M. Graham Lopez, Jeff R. Hammond, Jack C. Wells, Tom Gibbs, Timothy B. Costa

Proceedings of the Driving Scientific and Engineering Discoveries Through the Integration of Experiment, Big Data, and Modeling and Simulation, 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

2020

ProtTrans: Towards Cracking the Language of Life's Code Through Self-Supervised Deep Learning and High Performance Computing.

Ahmed Elnaggar, Michael Heinzinger, Christian Dallago, Ghalia Rehawi, Yu Wang, Llion Jones, Tom Gibbs, Tamas Feher, Christoph Angerer, Martin Steinegger, Debsindhu Bhowmik, Burkhard Rost

CoRR, 2020

2019

Enabling real-time multi-messenger astrophysics discoveries with deep learning.

E. A. Huerta, Gabrielle Allen, Igor Andreoni, Javier Mauricio Antelis, Etienne Bachelet, G. Bruce Berriman, Federica B. Bianco, Rahul Biswas, Matias Carrasco Kind, Kyle Chard, Minsik Cho, Philip S. Cowperthwaite, Zachariah B. Etienne, Maya Fishbach, Francisco Förster, Daniel George, Tom Gibbs, Matthew J. Graham, William Gropp, Robert A. Gruendl, Anushri Gupta, Roland Haas, Sarah Habib, Elise Jennings, Margaret W. G. Johnson, Erik Katsavounidis, Daniel S. Katz, Asad Khan, Volodymyr V. Kindratenko, William T. C. Kramer, Xin Liu, Ashish Mahabal, Zsuzsa Márka, Kenton McHenry, Jonah Miller, Claudia Moreno, Mark S. Neubauer, Steve Oberlin, Alexander R. Olivas, Donald Petravick, Adam Rebei, Shawn Rosofsky, Milton Ruiz, Aaron Saxton, Bernard F. Schutz, Alexander G. Schwing, Ed Seidel, Stuart L. Shapiro, Hongyu Shen, Yue Shen, Leo Singer, Brigitta M. Sipocz, Lunan Sun, John Towns, Antonios Tsokaros, Wei Wei, Jack Wells, Timothy J. Williams, Jinjun Xiong, Zhizhen Zhao

CoRR, 2019

Deep Learning for Multi-Messenger Astrophysics: A Gateway for Discovery in the Big Data Era.

Gabrielle Allen, Igor Andreoni, Etienne Bachelet, G. Bruce Berriman, Federica B. Bianco, Rahul Biswas, Matias Carrasco Kind, Kyle Chard, Minsik Cho, Philip S. Cowperthwaite, Zachariah B. Etienne, Daniel George, Tom Gibbs, Matthew J. Graham, William Gropp, Anushri Gupta, Roland Haas, E. A. Huerta, Elise Jennings, Daniel S. Katz, Asad Khan, Volodymyr V. Kindratenko, William T. C. Kramer, Xin Liu, Ashish Mahabal, Kenton McHenry, J. M. Miller, Mark S. Neubauer, Steve Oberlin, Alexander Reinefeld, Shawn Rosofsky, Milton Ruiz, Aaron Saxton, Bernard F. Schutz, Alexander G. Schwing, Ed Seidel, Stuart L. Shapiro, Hongyu Shen, Yue Shen, Brigitta Miksztai-Réthey, Lunan Sun, John Towns, Antonios Tsokaros, Wei Wei, Jack Wells, Timothy J. Williams, Jinjun Xiong, Zhizhen Zhao

CoRR, 2019