Thorsten Kurth

According to our database, Thorsten Kurth authored at least 52 papers between 2016 and 2024.

Collaborative distances:

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

2024

Modulated Adaptive Fourier Neural Operators for Temporal Interpolation of Weather Forecasts.

Jussi Leinonen, Boris Bonev, Thorsten Kurth, Yair Cohen

CoRR, 2024

Toward Capturing Genetic Epistasis From Multivariate Genome-Wide Association Studies Using Mixed-Precision Kernel Ridge Regression.

Hatem Ltaief, Rabab Alomairy, Qinglei Cao, Jie Ren, Lotfi Slim, Thorsten Kurth, Benedikt Dorschner, Salim Bougouffa, Rached Abdelkhalak, David E. Keyes

CoRR, 2024

Huge Ensembles Part I: Design of Ensemble Weather Forecasts using Spherical Fourier Neural Operators.

Ankur Mahesh, William D. Collins, Boris Bonev, Noah D. Brenowitz, Yair Cohen, Joshua Elms, Peter Harrington, Karthik Kashinath, Thorsten Kurth, Joshua North, Travis A. O'Brien, Michael S. Pritchard, David Pruitt, Mark Risser, Shashank Subramanian, Jared Willard

CoRR, 2024

Huge Ensembles Part II: Properties of a Huge Ensemble of Hindcasts Generated with Spherical Fourier Neural Operators.

Ankur Mahesh, William D. Collins, Boris Bonev, Noah D. Brenowitz, Yair Cohen, Peter Harrington, Karthik Kashinath, Thorsten Kurth, Joshua North, Travis A. O'Brien, Michael S. Pritchard, David Pruitt, Mark Risser, Shashank Subramanian, Jared Willard

CoRR, 2024

Coupled Ocean-Atmosphere Dynamics in a Machine Learning Earth System Model.

Chenggong Wang, Michael S. Pritchard, Noah D. Brenowitz, Yair Cohen, Boris Bonev, Thorsten Kurth, Dale R. Durran, Jaideep Pathak

CoRR, 2024

A Practical Probabilistic Benchmark for AI Weather Models.

Noah D. Brenowitz, Yair Cohen, Jaideep Pathak, Ankur Mahesh, Boris Bonev, Thorsten Kurth, Dale R. Durran, Peter Harrington, Michael S. Pritchard

CoRR, 2024

Neural Operators with Localized Integral and Differential Kernels.

Miguel Liu-Schiaffini, Julius Berner, Boris Bonev, Thorsten Kurth, Kamyar Azizzadenesheli, Anima Anandkumar

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Advancing Parsimonious Deep Learning Weather Prediction using the HEALPix Mesh.

Matthias Karlbauer, Nathaniel Cresswell-Clay, Raul A. Moreno, Dale R. Durran, Thorsten Kurth, Martin V. Butz

CoRR, 2023

ClimSim: An open large-scale dataset for training high-resolution physics emulators in hybrid multi-scale climate simulators.

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 R. 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.

CoRR, 2023

Scaling Resolution of Gigapixel Whole Slide Images Using Spatial Decomposition on Convolutional Neural Networks.

Aristeidis Tsaris, Joshua Romero, Thorsten Kurth, Jacob D. Hinkle, Hong-Jun Yoon, Feiyi Wang, Sajal Dash, Georgia D. Tourassi

Proceedings of the Platform for Advanced Scientific Computing Conference, 2023

FourCastNet: Accelerating Global High-Resolution Weather Forecasting Using Adaptive Fourier Neural Operators.

Thorsten Kurth, Shashank Subramanian, Peter Harrington, Jaideep Pathak, Morteza Mardani, David Hall, Andrea Miele, Karthik Kashinath, Anima Anandkumar

Proceedings of the Platform for Advanced Scientific Computing Conference, 2023

ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation.

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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Spherical Fourier Neural Operators: Learning Stable Dynamics on the Sphere.

Boris Bonev, Thorsten Kurth, Christian Hundt, Jaideep Pathak, Maximilian Baust, Karthik Kashinath, Anima Anandkumar

Proceedings of the International Conference on Machine Learning, 2023

Clinical validation of rapid GPU-enabled DTI tractography of the brain.

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

Proceedings of the High Performance Computing for Imaging 2023, 2023

2022

FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators.

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

CoRR, 2022

NERSC Job Script Generator.

Robin Shao, Thorsten Kurth, Zhengji Zhao

Proceedings of the IEEE/ACM International Workshop on HPC User Support Tools, 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

MLPerf HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems.

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

CoRR, 2021

Hierarchical Roofline Performance Analysis for Deep Learning Applications.

Charlene Yang, Yunsong Wang, Thorsten Kurth, Steven Farrell, Samuel Williams

Proceedings of the Intelligent Computing, 2021

MLPerf™ HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems.

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

Proceedings of the IEEE/ACM Workshop on Machine Learning in High Performance Computing Environments, 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

Using Machine Learning to Augment Coarse-Grid Computational Fluid Dynamics Simulations.

Jaideep Pathak, Mustafa Mustafa, Karthik Kashinath, Emmanuel Motheau, Thorsten Kurth, Marcus Day

CoRR, 2020

Hierarchical Roofline analysis for GPUs: Accelerating performance optimization for the NERSC-9 Perlmutter system.

Charlene Yang, Thorsten Kurth, Samuel Williams

Concurr. Comput. Pract. Exp., 2020

Time-Based Roofline for Deep Learning Performance Analysis.

Yunsong Wang, Charlene Yang, Steven Farrell, Yan Zhang, Thorsten Kurth, Samuel Williams

Proceedings of the Fourth IEEE/ACM Workshop on Deep Learning on Supercomputers, 2020

2019

Highly-scalable, physics-informed GANs for learning solutions of stochastic PDEs.

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

CoRR, 2019

TensorFlow at Scale: Performance and productivity analysis of distributed training with Horovod, MLSL, and Cray PE ML.

Thorsten Kurth, Mikhail Smorkalov, Peter Mendygral, Srinivas Sridharan, Amrita Mathuriya

Concurr. Comput. Pract. Exp., 2019

Eigensolver performance comparison on Cray XC systems.

Brandon Cook, Thorsten Kurth, Jack Deslippe, Pierre Carrier, Nick Hill, Nathan Wichmann

Concurr. Comput. Pract. Exp., 2019

Acceleration of Scientific Deep Learning Models on Heterogeneous Computing Platform with Intel^® FPGAs.

Chao Jiang, Dave Ojika, Thorsten Kurth, Prabhat, Sofia Vallecorsa, Bhavesh Patel, Herman Lam

Proceedings of the High Performance Computing, 2019

Highly-Ccalable, Physics-Informed GANs for Learning Solutions of Stochastic PDEs.

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

Proceedings of the Third IEEE/ACM Workshop on Deep Learning on Supercomputers, 2019

Performance Portability of a Wilson Dslash Stencil Operator Mini-App Using Kokkos and SYCL.

Bálint Joó, Thorsten Kurth, Michael A. Clark, Jeongnim Kim, Christian Robert Trott, Dan Ibanez, Daniel Sunderland, Jack Deslippe

Proceedings of the 2019 IEEE/ACM International Workshop on Performance, 2019

PCS: A Productive Computational Science Platform.

David Ojika, Ann Gordon-Ross, Herman Lam, Shinjae Yoo, Younggang Cui, Zhihua Dong, Kirstin Kleese van Dam, Seyong Lee, Thorsten Kurth

Proceedings of the 17th International Conference on High Performance Computing & Simulation, 2019

2018

A per-cent-level determination of the nucleon axial coupling from quantum chromodynamics.

Chin-Chen Chang, Amy N. Nicholson, Enrico Rinaldi, Evan Berkowitz, Nicolas Garron, D. A. Brantley, H. Monge-Camacho, C. J. Monahan, Chris Bouchard, Michael A. Clark, Bálint Joó, Thorsten Kurth, Konstantinos Orginos, Pavlos Vranas, André Walker-Loud

Nat., 2018

Simulating the weak death of the neutron in a femtoscale universe with near-Exascale computing.

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

CoRR, 2018

Preparing NERSC users for Cori, a Cray XC40 system with Intel many integrated cores.

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

Concurr. Comput. Pract. Exp., 2018

Lessons Learned from Optimizing Kernels for Adaptive Aggregation Multi-grid Solvers in Lattice QCD.

Bálint Joó, Thorsten Kurth

Proceedings of the High Performance Computing, 2018

Sparse CSB_Coo Matrix-Vector and Matrix-Matrix Performance on Intel Xeon Architectures.

Brandon Cook, Charlene Yang, Thorsten Kurth, Jack Deslippe

Proceedings of the High Performance Computing, 2018

Exascale deep learning for climate analytics.

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

Proceedings of the International Conference for High Performance Computing, 2018

A Case Study for Performance Portability Using OpenMP 4.5.

Rahulkumar Gayatri, Charlene Yang, Thorsten Kurth, Jack Deslippe

Proceedings of the Accelerator Programming Using Directives - 5th International Workshop, 2018

Simulating the <i>weak</i> death of the Neutron in a femtoscale universe with near-exascale computing.

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

Proceedings of the International Conference for High Performance Computing, 2018

A Metric for Evaluating Supercomputer Performance in the Era of Extreme Heterogeneity.

Brian Austin, Christopher S. Daley, Douglas Doerfler, Jack Deslippe, Brandon Cook, Brian Friesen, Thorsten Kurth, Charlene Yang, Nicholas J. Wright

Proceedings of the 2018 IEEE/ACM Performance Modeling, 2018

2017

Improved treatment of exact exchange in Quantum ESPRESSO.

Taylor Barnes, Thorsten Kurth, Pierre Carrier, Nathan Wichmann, David Prendergast, Paul R. C. Kent, Jack Deslippe

Comput. Phys. Commun., 2017

Scaling GRPC Tensorflow on 512 nodes of Cori Supercomputer.

Amrita Mathuriya, Thorsten Kurth, Vivek Rane, Mustafa Mustafa, Lei Shao, Debbie Bard, Prabhat, Victor W. Lee

CoRR, 2017

Deep Neural Networks for Physics Analysis on low-level whole-detector data at the LHC.

Wahid Bhimji, Steven Andrew Farrell, Thorsten Kurth, Michela Paganini, Prabhat, Evan Racah

CoRR, 2017

Analyzing Performance of Selected NESAP Applications on the Cori HPC System.

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

Proceedings of the High Performance Computing, 2017

Performance Variability on Xeon Phi.

Brandon Cook, Thorsten Kurth, Brian Austin, Samuel Williams, Jack Deslippe

Proceedings of the High Performance Computing, 2017

Deep learning at 15PF: supervised and semi-supervised classification for scientific data.

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

Proceedings of the International Conference for High Performance Computing, 2017

2016

Optimization of the Sparse Matrix-Vector Products of an IDR Krylov Iterative Solver in EMGeo for the Intel KNL Manycore Processor.

Tareq M. Malas, Thorsten Kurth, Jack Deslippe

Proceedings of the High Performance Computing, 2016

Optimizing Wilson-Dirac Operator and Linear Solvers for Intel® KNL.

Bálint Joó, Dhiraj D. Kalamkar, Thorsten Kurth, Karthikeyan Vaidyanathan, Aaron Walden

Proceedings of the High Performance Computing, 2016

Applying the Roofline Performance Model to the Intel Xeon Phi Knights Landing Processor.

Douglas Doerfler, Jack Deslippe, Samuel Williams, Leonid Oliker, Brandon Cook, Thorsten Kurth, Mathieu Lobet, Tareq M. Malas, Jean-Luc Vay, Henri Vincenti

Proceedings of the High Performance Computing, 2016

Evaluating and Optimizing the NERSC Workload on Knights Landing.

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

Proceedings of the 7th International Workshop on Performance Modeling, 2016

MPI usage at NERSC: Present and Future.

Alice Koniges, Brandon Cook, Jack Deslippe, Thorsten Kurth, Hongzhang Shan

Proceedings of the 23rd European MPI Users' Group Meeting, EuroMPI 2016, 2016

OpenMP Parallelization and Optimization of Graph-Based Machine Learning Algorithms.

Zhaoyi Meng, Alice Koniges, Yun (Helen) He, Samuel Williams, Thorsten Kurth, Brandon Cook, Jack Deslippe, Andrea L. Bertozzi

Proceedings of the OpenMP: Memory, Devices, and Tasks, 2016