Matthew R. Norman

According to our database, Matthew R. Norman authored at least 25 papers between 2011 and 2023.

Collaborative distances:

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

2023

Portable C++ Code that can Look and Feel Like Fortran Code with Yet Another Kernel Launcher (YAKL).

Matthew R. Norman, Isaac Lyngaas, Abhishek Bagusetty, Mark A. Berrill

Int. J. Parallel Program., October, 2023

Experiences Readying Applications for Exascale.

Paul T. Bauman, Reuben D. Budiardja, Dmytro Bykov, Noel Chalmers, Jacqueline Chen, Nicholas Curtis, Marc Day, Markus Eisenbach, Lucas Esclapez, Alessandro Fanfarillo, William Freitag, Nicholas Frontiere, Antigoni Georgiadou, Joseph Glenski, Kalyana C. Gottiparthi, Marc T. Henry de Frahan, Gustav R. Jansen, Wayne Joubert, Justin G. Lietz, Jakub Kurzak, Nicholas Malaya, Bronson Messer, Damon McDougall, Paul Mullowney, Stephen Nichols, Matthew R. Norman, Thomas Papatheodore, Jon S. Rood, Philip C. Roth, Sarat Sreepathi, James B. White III, Noah Wolfe

CoRR, 2023

Perspectives on AI Architectures and Co-design for Earth System Predictability.

Maruti K. Mudunuru, James A. Ang, Mahantesh Halappanavar, Simon D. Hammond, Maya B. Gokhale, James C. Hoe, Tushar Krishna, Sarat Sreepathi, Matthew R. Norman, Ivy Bo Peng, Philip W. Jones

CoRR, 2023

The Simple Cloud-Resolving E3SM Atmosphere Model Running on the Frontier Exascale System.

Mark Taylor, Peter M. Caldwell, Luca Bertagna, Conrad Clevenger, Aaron Donahue, James G. Foucar, Oksana Guba, Benjamin R. Hillman, Noel Keen, Jayesh Krishna, Matthew R. Norman, Sarat Sreepathi, Christopher Terai, James B. White III, Andrew G. Salinger, Renata B. McCoy, Lai-yung Ruby Leung, David C. Bader, Danqing Wu

Proceedings of the International Conference for High Performance Computing, 2023

Experiences readying applications for Exascale.

Nicholas Malaya, Bronson Messer, Joseph Glenski, Antigoni Georgiadou, Justin Lietz, Kalyana C. Gottiparthi, Marc Day, Jackie Chen, Jon S. Rood, Lucas Esclapez, James B. White III, Gustav R. Jansen, Nicholas Curtis, Stephen Nichols, Jakub Kurzak, Noel Chalmers, Chip Freitag, Paul T. Bauman, Alessandro Fanfarillo, Reuben D. Budiardja, Thomas Papatheodore, Nicholas Frontiere, Damon McDougall, Matthew R. Norman, Sarat Sreepathi, Philip C. Roth, Dmytro Bykov, Noah Wolfe, Paul Mullowney, Markus Eisenbach, Marc T. Henry de Frahan, Wayne Joubert

Proceedings of the International Conference for High Performance Computing, 2023

Physics guided machine learning for multi-material decomposition of tissues from dual-energy CT scans of simulated breast models with calcifications.

Muralikrishnan Gopalakrishnan Meena, Amirkoushyar Ziabari, Singanallur V. Venkatakrishnan, Isaac Lyngaas, Matthew R. Norman, Bálint Joó, Thomas L. Beck, Charles A. Bouman, Anuj J. Kapadia, Xiao Wang

Proceedings of the High Performance Computing for Imaging 2023, 2023

2022

Unprecedented cloud resolution in a GPU-enabled full-physics atmospheric climate simulation on OLCF's summit supercomputer.

Matthew R. Norman, David A. Bader, Christopher Eldred, Walter M. Hannah, Benjamin R. Hillman, Christopher R. Jones, Jungmin M. Lee, L. Ruby Leung, Isaac Lyngaas, Kyle G. Pressel, Sarat Sreepathi, Mark A. Taylor, Xingqiu Yuan

Int. J. High Perform. Comput. Appl., 2022

SAM++: Porting the E3SM-MMF cloud resolving model using a C++ portability library.

Isaac Lyngaas, Matthew R. Norman, Youngsung Kim

Int. J. High Perform. Comput. Appl., 2022

2021

TRITON: A Multi-GPU open source 2D hydrodynamic flood model.

Mario Morales-Hernández, Md Bulbul Sharif, Alfred J. Kalyanapu, Sheikh K. Ghafoor, Tigstu T. Dullo, Sudershan Gangrade, Shih-Chieh Kao, Matthew R. Norman, Katherine J. Evans

Environ. Model. Softw., 2021

Progress towards accelerating the unified model on hybrid multi-core systems.

Wei Zhang, Min Xu, Katherine J. Evans, Matthew R. Norman, Mario Morales-Hernández, Salil Mahajan, Adrian Hill, James Manners, Ben Shipway, Christopher M. Maynard

Proceedings of the PASC '21: Platform for Advanced Scientific Computing Conference, 2021

2020

A Holistic Algorithmic Approach to Improving Accuracy, Robustness, and Computational Efficiency for Atmospheric Dynamics.

Matthew R. Norman, Jeffrey M. Larkin

SIAM J. Sci. Comput., 2020

Pre-exascale accelerated application development: The ORNL Summit experience.

Lixiang Luo, Tjerk P. Straatsma, Luis Enrique Aguilar-Suárez, Ria Broer, Dmytro Bykov, Eduardo F. D'Azevedo, Shirin S. Faraji, Kalyana C. Gottiparthi, Coen de Graaf, James Austin Harris, Remco W. A. Havenith, Hans Jørgen Aagard Jensen, Wayne Joubert, R. K. Kathir, Jeff Larkin, Ying Wai Li, Dmitry I. Lyakh, O. E. Bronson Messer, Matthew R. Norman, Joseph C. Oefelein, Ramanan Sankaran, Andreas F. Tillack, Ashleigh L. Barnes, Lucas Visscher, Jack C. Wells, Meilani Wibowo

IBM J. Res. Dev., 2020

2019

Ongoing solution reproducibility of earth system models as they progress toward exascale computing.

Salil Mahajan, Katherine J. Evans, Joseph H. Kennedy, Min Xu, Matthew R. Norman, Marcia L. Branstetter

Int. J. High Perform. Comput. Appl., 2019

Performance analysis of fully explicit and fully implicit solvers within a spectral element shallow-water atmosphere model.

Katherine J. Evans, Richard K. Archibald, David J. Gardner, Matthew R. Norman, Mark A. Taylor, Carol S. Woodward, Patrick H. Worley

Int. J. High Perform. Comput. Appl., 2019

A Multivariate Approach to Ensure Statistical Reproducibility of Climate Model Simulations.

Salil Mahajan, Katherine J. Evans, Joseph H. Kennedy, Min Xu, Matthew R. Norman

Proceedings of the Platform for Advanced Scientific Computing Conference, 2019

2017

Exploring an Ensemble-Based Approach to Atmospheric Climate Modeling and Testing at Scale.

Salil Mahajan, Abigail L. Gaddis, Katherine J. Evans, Matthew R. Norman

Proceedings of the International Conference on Computational Science, 2017

2015

A case study of CUDA FORTRAN and OpenACC for an atmospheric climate kernel.

Matthew R. Norman, Jeffrey M. Larkin, Aaron Vose, Katherine J. Evans

J. Comput. Sci., 2015

Hermite WENO limiting for multi-moment finite-volume methods using the ADER-DT time discretization for 1-D systems of conservation laws.

Matthew R. Norman

J. Comput. Phys., 2015

Accelerated application development: The ORNL Titan experience.

Wayne Joubert, Rick Archibald, Mark A. Berrill, W. Michael Brown, Markus Eisenbach, Ray W. Grout, Jeff Larkin, John M. Levesque, Bronson Messer, Matthew R. Norman, Bobby Philip, Ramanan Sankaran, Arnold N. Tharrington, John A. Turner

Comput. Electr. Eng., 2015

Developing A Large Time Step, Robust, and Low Communication Multi-Moment PDE Integration Scheme for Exascale Applications.

Matthew R. Norman

Proceedings of the International Conference on Computational Science, 2015

2014

A WENO-limited, ADER-DT, finite-volume scheme for efficient, robust, and communication-avoiding multi-dimensional transport.

Matthew R. Norman

J. Comput. Phys., 2014

2013

Algorithmic improvements for schemes using the ADER time discretization.

Matthew R. Norman

J. Comput. Phys., 2013

Progress towards accelerating HOMME on hybrid multi-core systems.

Ilene Carpenter, Rick Archibald, Katherine J. Evans, Jeffrey M. Larkin, Paulius Micikevicius, Matthew R. Norman, James Rosinski, Jim Schwarzmeier, Mark A. Taylor

Int. J. High Perform. Comput. Appl., 2013

2012

Multi-moment ADER-Taylor methods for systems of conservation laws with source terms in one dimension.

Matthew R. Norman, H. Finkel

J. Comput. Phys., 2012

2011

A low communication and large time step explicit finite-volume solver for non-hydrostatic atmospheric dynamics.

Matthew R. Norman, Ramachandran D. Nair, Fredrick H. M. Semazzi

J. Comput. Phys., 2011