Thorsten Kurth

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 54

Top Topics

Weather Forecasting

Computational Science

Convolutional Neural Networks

Top Venues

Concurr. Comput. Pract. Exp.

Publications

Miguel Liu-Schiaffini, Julius Berner, Boris Bonev, Thorsten Kurth, Kamyar Azizzadenesheli, Anima Anandkumar
Neural Operators with Localized Integral and Differential Kernels. CoRR (2024)
Chenggong Wang, Michael S. Pritchard, Noah D. Brenowitz, Yair Cohen, Boris Bonev, Thorsten Kurth, Dale R. Durran, Jaideep Pathak
Coupled Ocean-Atmosphere Dynamics in a Machine Learning Earth System Model. CoRR (2024)
Noah D. Brenowitz, Yair Cohen, Jaideep Pathak, Ankur Mahesh, Boris Bonev, Thorsten Kurth, Dale R. Durran, Peter Harrington, Michael S. Pritchard
A Practical Probabilistic Benchmark for AI Weather Models. CoRR (2024)
Boris Bonev, Thorsten Kurth, Christian Hundt, Jaideep Pathak, Maximilian Baust, Karthik Kashinath, Anima Anandkumar
Spherical Fourier Neural Operators: Learning Stable Dynamics on the Sphere. ICML (2023)
Sungduk Yu, Walter M. Hannah, Liran Peng, Jerry Lin, Mohamed Aziz Bhouri, Ritwik Gupta, Björn Lütjens, Justus C. Will, Gunnar Behrens, Julius Busecke, Nora Loose, Charles Stern, Tom Beucler, Bryce E. Harrop, Benjamin R. Hillman, Andrea M. Jenney, Savannah L. Ferretti, Nana Liu, Animashree Anandkumar, Noah D. Brenowitz, Veronika Eyring, Nicholas Geneva, Pierre Gentine, Stephan Mandt, Jaideep Pathak, Akshay Subramaniam, Carl Vondrick, Rose Yu, Laure Zanna, Tian Zheng, Ryan Abernathey, Fiaz Ahmed, David C. Bader, Pierre Baldi, Elizabeth A. Barnes, Christopher S. Bretherton, Peter M. Caldwell, Wayne Chuang, Yilun Han, Yu Huang, Fernando Iglesias-Suarez, Sanket R. Jantre, Karthik Kashinath, Marat Khairoutdinov, Thorsten Kurth, Nicholas J. Lutsko, Po-Lun Ma, Griffin Mooers, J. David Neelin, David A. Randall, Sara Shamekh, Mark Taylor, Nathan M. Urban, Janni Yuval, Guang Zhang, Mike Pritchard
ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation. NeurIPS (2023)
Aristeidis Tsaris, Joshua Romero, Thorsten Kurth, Jacob D. Hinkle, Hong-Jun Yoon, Feiyi Wang, Sajal Dash, Georgia D. Tourassi
Scaling Resolution of Gigapixel Whole Slide Images Using Spatial Decomposition on Convolutional Neural Networks. PASC (2023)
Sungduk Yu, Walter M. Hannah, Liran Peng, Mohamed Aziz Bhouri, Ritwik Gupta, Jerry Lin, Björn Lütjens, Justus C. Will, Tom Beucler, Bryce E. Harrop, Benjamin R. Hillman, Andrea M. Jenney, Savannah L. Ferretti, Nana Liu, Anima Anandkumar, Noah D. Brenowitz, Veronika Eyring, Pierre Gentine, Stephan Mandt, Jaideep Pathak, Carl Vondrick, Rose Yu, Laure Zanna, Ryan P. Abernathey, Fiaz Ahmed, David C. Bader, Pierre Baldi, Elizabeth A. Barnes, Gunnar Behrens, Christopher S. Bretherton, Julius J. M. Busecke, Peter M. Caldwell, Wayne Chuang, Yilun Han, Yu Huang, Fernando Iglesias-Suarez, Sanket Jantre, Karthik Kashinath, Marat Khairoutdinov, Thorsten Kurth, Nicholas J. Lutsko, Po-Lun Ma, Griffin Mooers, J. David Neelin, David A. Randall, Sara Shamekh, Akshay Subramaniam, Mark A. Taylor, et al.
ClimSim: An open large-scale dataset for training high-resolution physics emulators in hybrid multi-scale climate simulators. CoRR (2023)
Boris Bonev, Thorsten Kurth, Christian Hundt, Jaideep Pathak, Maximilian Baust, Karthik Kashinath, Anima Anandkumar
Spherical Fourier Neural Operators: Learning Stable Dynamics on the Sphere. CoRR (2023)
Matthias Karlbauer, Nathaniel Cresswell-Clay, Raul A. Moreno, Dale R. Durran, Thorsten Kurth, Martin V. Butz
Advancing Parsimonious Deep Learning Weather Prediction using the HEALPix Mesh. CoRR (2023)
Thorsten Kurth, Shashank Subramanian, Peter Harrington, Jaideep Pathak, Morteza Mardani, David Hall, Andrea Miele, Karthik Kashinath, Anima Anandkumar
FourCastNet: Accelerating Global High-Resolution Weather Forecasting Using Adaptive Fourier Neural Operators. PASC (2023)
Felix Liu, Vanitha Sankaranarayanan, Javier E. Villanueva-Meyer, Shawn Hervey-Jumper, James Hawkins, Pablo F. Damasceno, Mauro Bisson, Joshua Romero, Thorsten Kurth, Massimiliano Fatica, Eleftherios Garyfallidis, Ariel Rokem, Jason C. Crane, Sharmila Majumdar
Clinical validation of rapid GPU-enabled DTI tractography of the brain. High Performance Computing for Imaging (2023)
Thorsten Kurth, Shashank Subramanian, Peter Harrington, Jaideep Pathak, Morteza Mardani, David Hall, Andrea Miele, Karthik Kashinath, Animashree Anandkumar
FourCastNet: Accelerating Global High-Resolution Weather Forecasting using Adaptive Fourier Neural Operators. CoRR (2022)
Jaideep Pathak, Shashank Subramanian, Peter Harrington, Sanjeev Raja, Ashesh Chattopadhyay, Morteza Mardani, Thorsten Kurth, David Hall, Zongyi Li, Kamyar Azizzadenesheli, Pedram Hassanzadeh, Karthik Kashinath, Animashree Anandkumar
FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators. CoRR (2022)
Charlene Yang, Yunsong Wang, Thorsten Kurth, Steven Farrell, Samuel Williams
Hierarchical Roofline Performance Analysis for Deep Learning Applications. SAI (2) (2021)
Steven Farrell, Murali Emani, Jacob Balma, Lukas Drescher, Aleksandr Drozd, Andreas Fink, Geoffrey C. Fox, David Kanter, Thorsten Kurth, Peter Mattson, Dawei Mu, Amit Ruhela, Kento Sato, Koichi Shirahata, Tsuguchika Tabaru, Aristeidis Tsaris, Jan Balewski, Ben Cumming, Takumi Danjo, Jens Domke, Takaaki Fukai, Naoto Fukumoto, Tatsuya Fukushi, Balazs Gerofi, Takumi Honda, Toshiyuki Imamura, Akihiko Kasagi, Kentaro Kawakami, Shuhei Kudo, Akiyoshi Kuroda, Maxime Martinasso, Satoshi Matsuoka, Henrique Mendonça, Kazuki Minami, Prabhat Ram, Takashi Sawada, Mallikarjun Shankar, Tom St. John, Akihiro Tabuchi, Venkatram Vishwanath, Mohamed Wahib, Masafumi Yamazaki, Junqi Yin
MLPerf™ HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems. MLHPC@SC (2021)
Steven Farrell, Murali Emani, Jacob Balma, Lukas Drescher, Aleksandr Drozd, Andreas Fink, Geoffrey C. Fox, David Kanter, Thorsten Kurth, Peter Mattson, Dawei Mu, Amit Ruhela, Kento Sato, Koichi Shirahata, Tsuguchika Tabaru, Aristeidis Tsaris, Jan Balewski, Ben Cumming, Takumi Danjo, Jens Domke, Takaaki Fukai, Naoto Fukumoto, Tatsuya Fukushi, Balazs Gerofi, Takumi Honda, Toshiyuki Imamura, Akihiko Kasagi, Kentaro Kawakami, Shuhei Kudo, Akiyoshi Kuroda, Maxime Martinasso, Satoshi Matsuoka, Henrique Mendonça, Kazuki Minami, Prabhat Ram, Takashi Sawada, Mallikarjun Shankar, Tom St. John, Akihiro Tabuchi, Venkatram Vishwanath, Mohamed Wahib, Masafumi Yamazaki, Junqi Yin
MLPerf HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems. CoRR (2021)
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
AI-driven multiscale simulations illuminate mechanisms of SARS-CoV-2 spike dynamics. Int. J. High Perform. Comput. Appl. 35 (5) (2021)
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
IMPECCABLE: Integrated Modeling PipelinE for COVID Cure by Assessing Better LEads. ICPP (2021)
Jaideep Pathak, Mustafa Mustafa, Karthik Kashinath, Emmanuel Motheau, Thorsten Kurth, Marcus Day
Using Machine Learning to Augment Coarse-Grid Computational Fluid Dynamics Simulations. CoRR (2020)
Yunsong Wang, Charlene Yang, Steven Farrell, Yan Zhang, Thorsten Kurth, Samuel Williams
Time-Based Roofline for Deep Learning Performance Analysis. DLS@SC (2020)
Charlene Yang, Thorsten Kurth, Samuel Williams
Hierarchical Roofline analysis for GPUs: Accelerating performance optimization for the NERSC-9 Perlmutter system. Concurr. Comput. Pract. Exp. 32 (20) (2020)
Aymen Al Saadi, Dario Alfè, Yadu N. Babuji, Agastya Bhati, Ben Blaiszik, Thomas S. Brettin, Kyle Chard, Ryan Chard, Peter V. Coveney, Anda Trifan, Alex Brace, Austin Clyde, Ian T. Foster, Tom Gibbs, Shantenu Jha, Kristopher Keipert, Thorsten Kurth, Dieter Kranzlmüller, Hyungro Lee, Zhuozhao Li, Heng Ma, André Merzky, Gerald Mathias, Alexander Partin, Junqi Yin, Arvind Ramanathan, Ashka Shah, Abraham C. Stern, Rick Stevens, Li Tan, Mikhail Titov, Aristeidis Tsaris, Matteo Turilli, Huub J. J. Van Dam, Shunzhou Wan, David Wifling
IMPECCABLE: Integrated Modeling PipelinE for COVID Cure by Assessing Better LEads. CoRR (2020)
Yunsong Wang, Charlene Yang, Steven Farrell, Yan Zhang, Thorsten Kurth, Samuel Williams
Time-Based Roofline for Deep Learning Performance Analysis. CoRR (2020)
Yunsong Wang, Charlene Yang, Steven Farrell, Thorsten Kurth, Samuel Williams
Hierarchical Roofline Performance Analysis for Deep Learning Applications. CoRR (2020)
Bálint Joó, Thorsten Kurth, Michael A. Clark, Jeongnim Kim, Christian Robert Trott, Dan Ibanez, Daniel Sunderland, Jack Deslippe
Performance Portability of a Wilson Dslash Stencil Operator Mini-App Using Kokkos and SYCL. P3HPC@SC (2019)
Chao Jiang, Dave Ojika, Thorsten Kurth, Prabhat, Sofia Vallecorsa, Bhavesh Patel, Herman Lam
FPGAs. ISC Workshops (2019)
David Ojika, Ann Gordon-Ross, Herman Lam, Shinjae Yoo, Younggang Cui, Zhihua Dong, Kirstin Kleese van Dam, Seyong Lee, Thorsten Kurth
PCS: A Productive Computational Science Platform. HPCS (2019)
Liu Yang, Prabhat, George E. Karniadakis, Sean Treichler, Thorsten Kurth, Keno Fischer, David A. Barajas-Solano, Joshua Romero, Valentin Churavy, Alexandre M. Tartakovsky, Michael Houston
Highly-Ccalable, Physics-Informed GANs for Learning Solutions of Stochastic PDEs. DLS@SC (2019)
Brandon Cook, Thorsten Kurth, Jack Deslippe, Pierre Carrier, Nick Hill, Nathan Wichmann
Eigensolver performance comparison on Cray XC systems. Concurr. Comput. Pract. Exp. 31 (16) (2019)
Liu Yang, Sean Treichler, Thorsten Kurth, Keno Fischer, David A. Barajas-Solano, Joshua Romero, Valentin Churavy, Alexandre M. Tartakovsky, Michael Houston, Prabhat, George E. Karniadakis
Highly-scalable, physics-informed GANs for learning solutions of stochastic PDEs. CoRR (2019)
Thorsten Kurth, Mikhail Smorkalov, Peter Mendygral, Srinivas Sridharan, Amrita Mathuriya
TensorFlow at Scale: Performance and productivity analysis of distributed training with Horovod, MLSL, and Cray PE ML. Concurr. Comput. Pract. Exp. 31 (16) (2019)
Thorsten Kurth, Sean Treichler, Joshua Romero, Mayur Mudigonda, Nathan Luehr, Everett H. Phillips, Ankur Mahesh, Michael A. Matheson, Jack Deslippe, Massimiliano Fatica, Prabhat, Michael Houston
Exascale deep learning for climate analytics. SC (2018)
Evan Berkowitz, Michael A. Clark, Arjun Singh Gambhir, Kenneth McElvain, Amy N. Nicholson, Enrico Rinaldi, Pavlos Vranas, André Walker-Loud, Chia-Cheng Chang, Bálint Joó, Thorsten Kurth, Kostas Orginos
death of the Neutron in a femtoscale universe with near-exascale computing. SC (2018)
Thorsten Kurth, Sean Treichler, Joshua Romero, Mayur Mudigonda, Nathan Luehr, Everett H. Phillips, Ankur Mahesh, Michael A. Matheson, Jack Deslippe, Massimiliano Fatica, Prabhat, Michael Houston
Exascale Deep Learning for Climate Analytics. CoRR (2018)
Chin-Chen Chang, Amy N. Nicholson, Enrico Rinaldi, Evan Berkowitz, N. Garron, D. A. Brantley, H. Monge-Camacho, C. J. Monahan, C. Bouchard, Michael A. Clark, Bálint Joó, Thorsten Kurth, Konstantinos Orginos, Pavlos Vranas, André Walker-Loud
A per-cent-level determination of the nucleon axial coupling from quantum chromodynamics. Nat. 558 (7708) (2018)
Yun (Helen) He, Brandon Cook, Jack Deslippe, Brian Friesen, Richard A. Gerber, Rebecca Hartman-Baker, Alice Koniges, Thorsten Kurth, Stephen Leak, Woo-Sun Yang, Zhengji Zhao, Eddie Baron, Peter Hauschildt
Preparing NERSC users for Cori, a Cray XC40 system with Intel many integrated cores. Concurr. Comput. Pract. Exp. 30 (1) (2018)
Brian Austin, Christopher S. Daley, Douglas Doerfler, Jack Deslippe, Brandon Cook, Brian Friesen, Thorsten Kurth, Charlene Yang, Nicholas J. Wright
A Metric for Evaluating Supercomputer Performance in the Era of Extreme Heterogeneity. PMBS@SC (2018)
Rahulkumar Gayatri, Charlene Yang, Thorsten Kurth, Jack Deslippe
A Case Study for Performance Portability Using OpenMP 4.5. WACCPD@SC (2018)
Bálint Joó, Thorsten Kurth
Lessons Learned from Optimizing Kernels for Adaptive Aggregation Multi-grid Solvers in Lattice QCD. ISC Workshops (2018)
Brandon Cook, Charlene Yang, Thorsten Kurth, Jack Deslippe
Sparse CSB_Coo Matrix-Vector and Matrix-Matrix Performance on Intel Xeon Architectures. ISC Workshops (2018)
Evan Berkowitz, Michael A. Clark, Arjun Singh Gambhir, Kenneth McElvain, Amy N. Nicholson, Enrico Rinaldi, Pavlos Vranas, André Walker-Loud, Chia-Cheng Chang, Bálint Joó, Thorsten Kurth, Kostas Orginos
Simulating the weak death of the neutron in a femtoscale universe with near-Exascale computing. CoRR (2018)
Taylor Barnes, Thorsten Kurth, Pierre Carrier, Nathan Wichmann, David Prendergast, Paul R. C. Kent, Jack Deslippe
Improved treatment of exact exchange in Quantum ESPRESSO. Comput. Phys. Commun. 214 (2017)
Thorsten Kurth, William Arndt, Taylor Barnes, Brandon Cook, Jack Deslippe, Douglas Doerfler, Brian Friesen, Yun (Helen) He, Tuomas Koskela, Mathieu Lobet, Tareq M. Malas, Leonid Oliker, Andrey Ovsyannikov, Samuel Williams, Woo-Sun Yang, Zhengji Zhao
Analyzing Performance of Selected NESAP Applications on the Cori HPC System. ISC Workshops (2017)
Brandon Cook, Thorsten Kurth, Brian Austin, Samuel Williams, Jack Deslippe
Performance Variability on Xeon Phi. ISC Workshops (2017)
Thorsten Kurth, Jian Zhang, Nadathur Satish, Evan Racah, Ioannis Mitliagkas, Md. Mostofa Ali Patwary, Tareq M. Malas, Narayanan Sundaram, Wahid Bhimji, Mikhail Smorkalov, Jack Deslippe, Mikhail Shiryaev, Srinivas Sridharan, Prabhat, Pradeep Dubey
Deep learning at 15PF: supervised and semi-supervised classification for scientific data. SC (2017)
Thorsten Kurth, Jian Zhang, Nadathur Satish, Ioannis Mitliagkas, Evan Racah, Md. Mostofa Ali Patwary, Tareq M. Malas, Narayanan Sundaram, Wahid Bhimji, Mikhail Smorkalov, Jack Deslippe, Mikhail Shiryaev, Srinivas Sridharan, Prabhat, Pradeep Dubey
Deep Learning at 15PF: Supervised and Semi-Supervised Classification for Scientific Data. CoRR (2017)
Amrita Mathuriya, Thorsten Kurth, Vivek Rane, Mustafa Mustafa, Lei Shao, Debbie Bard, Prabhat, Victor W. Lee
Scaling GRPC Tensorflow on 512 nodes of Cori Supercomputer. CoRR (2017)
Wahid Bhimji, Steven Andrew Farrell, Thorsten Kurth, Michela Paganini, Prabhat, Evan Racah
Deep Neural Networks for Physics Analysis on low-level whole-detector data at the LHC. CoRR (2017)
Bálint Joó, Dhiraj D. Kalamkar, Thorsten Kurth, Karthikeyan Vaidyanathan, Aaron Walden
Optimizing Wilson-Dirac Operator and Linear Solvers for Intel® KNL. ISC Workshops (2016)
Douglas Doerfler, Jack Deslippe, Samuel Williams, Leonid Oliker, Brandon Cook, Thorsten Kurth, Mathieu Lobet, Tareq M. Malas, Jean-Luc Vay, Henri Vincenti
Applying the Roofline Performance Model to the Intel Xeon Phi Knights Landing Processor. ISC Workshops (2016)
Alice Koniges, Brandon Cook, Jack Deslippe, Thorsten Kurth, Hongzhang Shan
MPI usage at NERSC: Present and Future. EuroMPI (2016)
Tareq M. Malas, Thorsten Kurth, Jack Deslippe
Optimization of the Sparse Matrix-Vector Products of an IDR Krylov Iterative Solver in EMGeo for the Intel KNL Manycore Processor. ISC Workshops (2016)
Taylor Barnes, Brandon Cook, Jack Deslippe, Douglas Doerfler, Brian Friesen, Yun (Helen) He, Thorsten Kurth, Tuomas Koskela, Mathieu Lobet, Tareq M. Malas, Leonid Oliker, Andrey Ovsyannikov, Abhinav Sarje, Jean-Luc Vay, Henri Vincenti, Samuel Williams, Pierre Carrier, Nathan Wichmann, Marcus Wagner, Paul R. C. Kent, Christopher Kerr, John M. Dennis
Evaluating and Optimizing the NERSC Workload on Knights Landing. PMBS@SC (2016)
Zhaoyi Meng, Alice Koniges, Yun (Helen) He, Samuel Williams, Thorsten Kurth, Brandon Cook, Jack Deslippe, Andrea L. Bertozzi
OpenMP Parallelization and Optimization of Graph-Based Machine Learning Algorithms. IWOMP (2016)