Optimisation of Patch Distribution Strategies for AMR Applications. - D. A. Beckingsale; O. F. J. Perks; W. P. Gaudin; J. A. Herdman; Stephen A. Jarvis (EPEW/UKPEW, 2012)

Performance Modelling of Magnetohydrodynamics Codes. - Robert F. Bird; Steven A. Wright 001; D. A. Beckingsale; Stephen A. Jarvis (EPEW/UKPEW, 2012)

Accelerating Hydrocodes with OpenACC, OpeCL and CUDA. - J. A. Herdman; W. P. Gaudin; Simon McIntosh-Smith; Michael Boulton; D. A. Beckingsale; A. C. Mallinson; Stephen A. Jarvis (SC Companion, 2012)

Analysing the influence of InfiniBand choice on OpenMPI memory consumption. - O. F. J. Perks; D. A. Beckingsale; A. S. Dawes; J. A. Herdman; Cyril Mazauric; Stephen A. Jarvis (HPCS, 2013)

Towards Automated Memory Model Generation Via Event Tracing. - O. F. J. Perks; D. A. Beckingsale; Simon D. Hammond; I. Miller; J. A. Herdman; A. Vadgama; Abhir H. Bhalerao; Ligang He; Stephen A. Jarvis (Comput. J., 2013)

Achieving portability and performance through OpenACC. - J. A. Herdman; W. P. Gaudin; Oliver Perks; D. A. Beckingsale; A. C. Mallinson; Stephen A. Jarvis (WACCPD@SC, 2014)

Resident Block-Structured Adaptive Mesh Refinement on Thousands of Graphics Processing Units. - David Beckingsale; Wayne P. Gaudin; Andrew Herdman; Stephen A. Jarvis (ICPP, 2015)

Towards scalable adaptive mesh refinement on future parallel architectures. - David Beckingsale (2015)

Fast Multi-parameter Performance Modeling. - Alexandru Calotoiu; David Beckingsale; Christopher W. Earl; Torsten Hoefler; Ian Karlin; Martin Schulz 001; Felix Wolf 001 (CLUSTER, 2016)

Caliper: performance introspection for HPC software stacks. - David Böhme; Todd Gamblin; David Beckingsale; Peer-Timo Bremer; Alfredo Giménez; Matthew P. LeGendre; Olga Pearce; Martin Schulz 001 (SC, 2016)

Flexible Data Aggregation for Performance Profiling. - David Böhme; David Beckingsale; Martin Schulz 001 (CLUSTER, 2017)

TeaLeaf: A Mini-Application to Enable Design-Space Explorations for Iterative Sparse Linear Solvers. - Simon McIntosh-Smith; Matthew Martineau; Tom Deakin; Grzegorz Pawelczak; Wayne P. Gaudin; Paul Garrett; Wei Liu; Richard P. Smedley-Stevenson; David Beckingsale (CLUSTER, 2017)

Apollo: Reusable Models for Fast, Dynamic Tuning of Input-Dependent Code. - David Beckingsale; Olga Pearce; Ignacio Laguna; Todd Gamblin (IPDPS, 2017)

Introduction. - Tom Scogland; David Beckingsale (Int. J. High Perform. Comput. Appl., 2018)

FuncyTuner: Auto-tuning Scientific Applications With Per-loop Compilation. - Tao Wang 077; Nikhil Jain; David Beckingsale; David Böhme; Frank Mueller 001; Todd Gamblin (ICPP, 2019)

Performance portable C++ programming with RAJA. - David Beckingsale; Richard D. Hornung; Tom Scogland; Arturo Vargas (PPoPP, 2019)

RAJA: Portable Performance for Large-Scale Scientific Applications. - David Beckingsale; Thomas R. W. Scogland; Jason Burmark; Rich Hornung; Holger Jones; William Killian; Adam J. Kunen; Olga Pearce; Peter Robinson 009; Brian S. Ryujin (P3HPC@SC, 2019)

Preparation and optimization of a diverse workload for a large-scale heterogeneous system. - Ian Karlin; Yoonho Park; Bronis R. de Supinski; Peng Wang; Bert Still; David Beckingsale; Robert Blake; Tong Chen 001; Guojing Cong; Carlos H. A. Costa; Johann Dahm; Giacomo Domeniconi; et al. (SC, 2019)

CodeSeer: input-dependent code variants selection via machine learning. - Tao Wang 077; Nikhil Jain; David Böhme; David Beckingsale; Frank Mueller 001; Todd Gamblin (ICS, 2020)

Umpire: Application-focused management and coordination of complex hierarchical memory. - D. A. Beckingsale; Marty McFadden; Johann Dahm; Ramesh Pankajakshan; Richard D. Hornung (IBM J. Res. Dev., 2020)

Artemis: Automatic Runtime Tuning of Parallel Execution Parameters Using Machine Learning. - Chad Wood; Giorgis Georgakoudis; David Beckingsale; David Poliakoff; Alfredo Giménez; Kevin A. Huck; Allen D. Malony; Todd Gamblin (ISC, 2021)

Extending OpenMP for Machine Learning-Driven Adaptation. - Chunhua Liao; Anjia Wang; Giorgis Georgakoudis; Bronis R. de Supinski; Yonghong Yan 001; David Beckingsale; Todd Gamblin (WACCPD@SC, 2021)

Machine Learning-Driven Adaptive OpenMP For Portable Performance on Heterogeneous Systems. - Giorgis Georgakoudis; Konstantinos Parasyris; Chunhua Liao; David Beckingsale; Todd Gamblin; Bronis R. de Supinski (CoRR, 2023)

An Exploration of Global Optimization Strategies for Autotuning OpenMP-based Codes. - Gregory Bolet; Giorgis Georgakoudis; Konstantinos Parasyris; Kirk W. Cameron; David Beckingsale; Todd Gamblin (IPDPS (Workshops), 2024)

Proteus: Portable Runtime Optimization of GPU Kernel Execution with Just-in-Time Compilation. - Giorgis Georgakoudis; Konstantinos Parasyris; David Beckingsale (CGO, 2025)