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)

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)

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)

Algorithmic improvements for schemes using the ADER time discretization. - Matthew R. Norman (J. Comput. Phys., 2013)

A WENO-limited, ADER-DT, finite-volume scheme for efficient, robust, and communication-avoiding multi-dimensional transport. - Matthew R. Norman (J. Comput. Phys., 2014)

Developing A Large Time Step, Robust, and Low Communication Multi-Moment PDE Integration Scheme for Exascale Applications. - Matthew R. Norman (ICCS, 2015)

Accelerated application development: The ORNL Titan experience. - Wayne Joubert; Rick Archibald; Mark A. Berrill; W. Michael Brown; Markus Eisenbach 002; Ray W. Grout; Jeff Larkin; John M. Levesque; Bronson Messer; Matthew R. Norman; Bobby Philip; Ramanan Sankaran; et al. (Comput. Electr. Eng., 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)

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)

Exploring an Ensemble-Based Approach to Atmospheric Climate Modeling and Testing at Scale. - Salil Mahajan; Abigail L. Gaddis; Katherine J. Evans; Matthew R. Norman (ICCS, 2017)

A Multivariate Approach to Ensure Statistical Reproducibility of Climate Model Simulations. - Salil Mahajan; Katherine J. Evans; Joseph H. Kennedy; Min Xu 004; Matthew R. Norman (PASC, 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)

Ongoing solution reproducibility of earth system models as they progress toward exascale computing. - Salil Mahajan; Katherine J. Evans; Joseph H. Kennedy; Min Xu 004; Matthew R. Norman; Marcia L. Branstetter (Int. J. High Perform. Comput. Appl., 2019)

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; et al. (IBM J. Res. Dev., 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)

Progress towards accelerating the unified model on hybrid multi-core systems. - Wei Zhang 261; Min Xu 004; Katherine J. Evans; Matthew R. Norman; Mario Morales-Hernández; Salil Mahajan; Adrian Hill; James Manners; Ben Shipway; Christopher M. Maynard (PASC, 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)

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)

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; et al. (Int. J. High Perform. Comput. Appl., 2022)

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 004 (High Performance Computing for Imaging, 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; et al. (SC, 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; et al. (SC, 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)

Experiences Readying Applications for Exascale. - Paul T. Bauman; Reuben D. Budiardja; Dmytro Bykov; Noel Chalmers; Jacqueline Chen; Nicholas Curtis; Marc Day; Markus Eisenbach 002; Lucas Esclapez; Alessandro Fanfarillo; William Freitag; Nicholas Frontiere; et al. (CoRR, 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., 2023)

Accelerated numerical modeling of shallow water flows with MPI, OpenACC, and GPUs. - Ayhan H. Saleem; Matthew R. Norman (Environ. Model. Softw., 2024)