Towards a Direct, By-Need Evaluator for Dependently Typed Languages. - David M. Rogers 001 (CoRR, 2015)

Efficient Primitives for Standard Tensor Linear Algebra. - David M. Rogers 001 (XSEDE, 2016)

Protein Conformational States - A First Principles Bayesian Method. - David M. Rogers 001 (Entropy, 2020)

Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19. - Atanu Acharya; Rupesh Agarwal; Matthew B. Baker; Jérôme Baudry; Debsindhu Bhowmik; Swen Böhm; Kendall G. Byler; Sam Yen-Chi Chen; Leighton Coates; Connor J. Cooper; Omar Demerdash; Isabella Daidone; et al. (J. Chem. Inf. Model., 2020)

Supercomputing Pipelines Search for Therapeutics Against COVID-19. - Josh Vincent Vermaas; Ada Sedova; Matthew B. Baker; Swen Boehm; David M. Rogers 001; Jeff Larkin; Jens Glaser; Micholas Dean Smith; Oscar R. Hernandez; Jeremy C. Smith (Comput. Sci. Eng., 2021)

High-throughput virtual laboratory for drug discovery using massive datasets. - Jens Glaser; Josh Vincent Vermaas; David M. Rogers 001; Jeff Larkin; Scott LeGrand; Swen Boehm; Matthew B. Baker; Aaron Scheinberg; Andreas F. Tillack; Mathialakan Thavappiragasam; Ada Sedova; Oscar R. Hernandez (Int. J. High Perform. Comput. Appl., 2021)

Understanding Strong Scaling on GPUs Using Empirical Performance Saturation Size. - David Eberius; Philip C. Roth; David M. Rogers 001 (P3HPC@SC, 2022)

DFT-FE 1.0: A massively parallel hybrid CPU-GPU density functional theory code using finite-element discretization. - Sambit Das; Phani Motamarri; Vishal Subramanian; David M. Rogers 001; Vikram Gavini (Comput. Phys. Commun., 2022)

Research Software Engineering at Oak Ridge National Laboratory. - Addi Malviya-Thakur; David E. Bernholdt; William F. Godoy; Gregory R. Watson; Mathieu Doucet; Mark A. Coletti; David M. Rogers 001; Marshall T. McDonnell; Jay Jay Billings; Barney Maccabe (Comput. Sci. Eng., 2022)

Hardware-Agnostic Interactive Exascale In Situ Visualization of Particle-In-Cell Simulations. - Felix Meyer; Benjamín Hernández; Richard Pausch; René Widera; David Groß; Sergei I. Bastrakov; Axel Huebl; Guido Juckeland; Jeffrey Kelling; Matt Leinhauser; David M. Rogers 001; Ulrich Schramm; et al. (PASC, 2023)

Frontier: Exploring Exascale. - Scott Atchley; Christopher Zimmer 001; John Lange; David E. Bernholdt; Verónica G. Melesse Vergara; Thomas Beck; Michael J. Brim; Reuben D. Budiardja; Sunita Chandrasekaran; Markus Eisenbach 002; Thomas M. Evans 001; Matthew Ezell; et al. (SC, 2023)

Large-Scale Materials Modeling at Quantum Accuracy: Ab Initio Simulations of Quasicrystals and Interacting Extended Defects in Metallic Alloys. - Sambit Das; Bikash Kanungo; Vishal Subramanian; Gourab Panigrahi; Phani Motamarri; David M. Rogers 001; Paul M. Zimmerman; Vikram Gavini (SC, 2023)

Ready for the Frontier: Preparing Applications for the World's First Exascale System. - Reuben D. Budiardja; Mark A. Berrill; Markus Eisenbach 002; Gustav R. Jansen; Wayne Joubert; Stephen Nichols; David M. Rogers 001; Arnold N. Tharrington; O. E. Bronson Messer (ISC, 2023)

A cast of thousands: How the IDEAS Productivity project has advanced software productivity and sustainability. - Lois Curfman McInnes; Michael A. Heroux; David E. Bernholdt; Anshu Dubey; Elsa Gonsiorowski; Rinku Gupta; Osni Marques; J. David Moulton; Hai Ah Nam; Boyana Norris; Elaine M. Raybourn; James M. Willenbring; et al. (CoRR, 2023)

Three practical workflow schedulers for easy maximum parallelism. - David M. Rogers 001 (Softw. Pract. Exp., 2023)

EZ: An efficient, charge conserving current deposition algorithm for electromagnetic particle-in-cell simulations. - Klaus Steiniger; René Widera; Sergey I. Bastrakov; Michael Bussmann; Sunita Chandrasekaran; Benjamín Hernández; Kristina Holsapple; Axel Huebl; Guido Juckeland; Jeffrey Kelling; Matt Leinhauser; Richard Pausch; et al. (Comput. Phys. Commun., 2023)

QuantumScents: Quantum-Mechanical Properties for 3.5k Olfactory Molecules. - Jackson W. Burns; David M. Rogers 001 (J. Chem. Inf. Model., 2023)

Scalable Training of Graph Foundation Models for Atomistic Materials Modeling: A Case Study with HydraGNN. - Massimiliano Lupo Pasini; Jong Youl Choi; Kshitij Mehta; Pei Zhang; David M. Rogers 001; Jonghyun Bae; Khaled Z. Ibrahim; Ashwin M. Aji; Karl W. Schulz; Jorda Polo; Prasanna Balaprakash (CoRR, 2024)

A Cast of Thousands: How the IDEAS Productivity Project Has Advanced Software Productivity and Sustainability. - Lois Curfman McInnes; Michael A. Heroux; David E. Bernholdt; Anshu Dubey; Elsa Gonsiorowski; Rinku Gupta; Osni Marques; J. David Moulton; Hai Ah Nam; Boyana Norris; Elaine M. Raybourn; James M. Willenbring; et al. (Comput. Sci. Eng., 2024)

Multi-level Monte Carlo methods in chemical applications with Lennard-Jones potentials and other landscapes with isolated singularities. - Alberto Bocchinfuso; David M. Rogers 001; Caio Alves; Jorge Ramirez; Dilipkumar N. Asthagiri; Thomas L. Beck; Juan M. Restrepo (Comput. Phys. Commun., 2025)

Scalable training of trustworthy and energy-efficient predictive graph foundation models for atomistic materials modeling: a case study with HydraGNN. - Massimiliano Lupo Pasini; Jong Youl Choi; Kshitij Mehta; Pei Zhang; David M. Rogers 001; Jonghyun Bae; Khaled Z. Ibrahim; Ashwin M. Aji; Karl W. Schulz; Jordà Polo; Prasanna Balaprakash (J. Supercomput., 2025)

Enabling Seamless Transitions from Experimental to Production HPC for Interactive Workflows. - Brian Etz; David M. Rogers 001; Michael J. Brim; Ketan Maheshwari; Kellen Leland; Tyler J. Skluzacek; Jack Lange; Daniel Pelfrey; Jordan Webb; Patrick Widener; Ryan Adamson; Christopher Zimmer 001; et al. (CoRR, 2025)