Application power profiling on IBM Blue Gene/Q. - Sean Wallace; Venkatram Vishwanath; Susan Coghlan; John R. Tramm; Zhiling Lan; Michael E. Papka (CLUSTER, 2013)

Performance Analysis of a Reduced Data Movement Algorithm for Neutron Cross Section Data in Monte Carlo Simulations. - John R. Tramm; Andrew R. Siegel; Benoit Forget; Colin Josey (EASC, 2014)

Power profiling of a reduced data movement algorithm for neutron cross section data in Monte Carlo simulations. - John R. Tramm; Kazutomo Yoshii; Andrew R. Siegel (Co-HPC@SC, 2014)

Data decomposition in Monte Carlo neutron transport simulations using global view arrays. - Nan Dun; Hajime Fujita 002; John R. Tramm; Andrew A. Chien; Andrew R. Siegel (Int. J. High Perform. Comput. Appl., 2015)

A task-based parallelism and vectorized approach to 3D Method of Characteristics (MOC) reactor simulation for high performance computing architectures. - John R. Tramm; Geoffrey Gunow; Tim He; Kord Smith; Benoit Forget; Andrew R. Siegel (Comput. Phys. Commun., 2016)

Application power profiling on IBM Blue Gene/Q. - Sean Wallace; Zhou Zhou 006; Venkatram Vishwanath; Susan Coghlan; John R. Tramm; Zhiling Lan; Michael E. Papka (Parallel Comput., 2016)

The Random Ray Method for neutral particle transport. - John R. Tramm; Kord Smith; Benoit Forget; Andrew R. Siegel (J. Comput. Phys., 2017)

Improving the scalabiliy of neutron cross-section lookup codes on multicore NUMA system. - Kazutomo Yoshii; John R. Tramm; Andrew R. Siegel; Peter H. Beckman (CoRR, 2019)

Evaluating the Performance of the hipSYCL Toolchain for HPC Kernels on NVIDIA V100 GPUs. - Brian Homerding; John R. Tramm (IWOCL, 2020)

Evaluation of Performance Portability of Applications and Mini-Apps across AMD, Intel and NVIDIA GPUs. - JaeHyuk Kwack; John R. Tramm; Colleen Bertoni; Yasaman Ghadar; Brian Homerding; Esteban Rangel; Christopher Knight 001; Scott Parker (P3HPC@SC, 2021)

Immortal rays: Rethinking random ray neutron transport on GPU architectures. - John R. Tramm; Andrew R. Siegel (Parallel Comput., 2021)

Just-in-Time Compilation and Link-Time Optimization for OpenMP Target Offloading. - Shilei Tian; Joseph Huber; John R. Tramm; Barbara M. Chapman; Johannes Doerfert (IWOMP, 2022)

Hardware Specialization: Estimating Monte Carlo Cross-Section Lookup Kernel Performance and Area. - Kazutomo Yoshii; John R. Tramm; Bryce Allen; Tomohiro Ueno; Kentaro Sano; Andrew R. Siegel; Pete Beckman (SC Workshops, 2023)

Ponte Vecchio Across the Atlantic: Single-Node Benchmarking of Two Intel GPU Systems. - Thomas Applencourt; Aditya Sadawarte; Servesh Muralidharan; Colleen Bertoni; JaeHyuk Kwack; Ye Luo; Esteban Rangel; John R. Tramm; Yasaman Ghadar; Arjen Tamerus; Chris Edsall; Tom Deakin (SC Workshops, 2024)

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs. - John R. Tramm; Paul K. Romano; Patrick C. Shriwise; Amanda Lund; Johannes Doerfert; Patrick Steinbrecher; Andrew R. Siegel; Gavin Ridley (CoRR, 2024)

Efficient algorithms for Monte Carlo particle transport on AI accelerator hardware. - John R. Tramm; Bryce Allen; Kazutomo Yoshii; Andrew R. Siegel; Leighton Wilson (Comput. Phys. Commun., 2024)

AI and HPC Applications on Leadership Computing Platforms: Performance and Scalability Studies. - JaeHyuk Kwack; Colleen Bertoni; Umesh Unnikrishnan; Riccardo Balin; Khalid Hossain; Yasaman Ghadar; Timothy J. Williams; Abhishek Bagusetty; Mathialakan Thavappiragasam; Väinö Hatanpää; Archit Vasan; John R. Tramm; et al. (IPDPS, 2025)

Integrating ytopt and libEnsemble to autotune OpenMC. - Xingfu Wu; John R. Tramm; Jeffrey Larson 001; John-Luke Navarro; Prasanna Balaprakash; Brice Videau; Michael Kruse; Paul D. Hovland; Valerie Taylor 001; Mary W. Hall (Int. J. High Perform. Comput. Appl., 2025)