Expressing Parallelism on Many-Core for Deterministic Discrete Ordinates Transport. - Tom Deakin; Simon McIntosh-Smith; Wayne P. Gaudin (CLUSTER, 2015)

Many-Core Acceleration of a Discrete Ordinates Transport Mini-App at Extreme Scale. - Tom Deakin; Simon McIntosh-Smith; Wayne P. Gaudin (ISC, 2016)

GPU-STREAM v2.0: Benchmarking the Achievable Memory Bandwidth of Many-Core Processors Across Diverse Parallel Programming Models. - Tom Deakin; James Price; Matt Martineau; Simon McIntosh-Smith (ISC Workshops, 2016)

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)

On the Mitigation of Cache Hostile Memory Access Patterns on Many-Core CPU Architectures. - Tom Deakin; Wayne P. Gaudin; Simon McIntosh-Smith (ISC Workshops, 2017)

UnSNAP: A Mini-App for Exploring the Performance of Deterministic Discrete Ordinates Transport on Unstructured Meshes. - Tom Deakin; Simon McIntosh-Smith; Justin Lovegrove; Richard P. Smedley-Stevenson; Andrew Hagues (CLUSTER, 2018)

Evaluating attainable memory bandwidth of parallel programming models via BabelStream. - Tom Deakin; James Price; Matt Martineau; Simon McIntosh-Smith (Int. J. Comput. Sci. Eng., 2018)

An improved parallelism scheme for deterministic discrete ordinates transport. - Tom Deakin; Simon McIntosh-Smith; Matt Martineau; Wayne P. Gaudin (Int. J. High Perform. Comput. Appl., 2018)

Performance Portability across Diverse Computer Architectures. - Tom Deakin; Simon McIntosh-Smith; James Price; Andrei Poenaru; Patrick Atkinson; Codrin Popa; Justin Salmon (P3HPC@SC, 2019)

A performance analysis of the first generation of HPC-optimized Arm processors. - Simon McIntosh-Smith; James Price; Tom Deakin; Andrei Poenaru (Concurr. Comput. Pract. Exp., 2019)

Evaluating the performance of HPC-style SYCL applications. - Tom Deakin; Simon McIntosh-Smith (IWOCL, 2020)

Hostile Cache Implications for Small, Dense Linear Solves. - Tom Deakin; James Cownie; Simon McIntosh-Smith; Justin Lovegrove; Richard P. Smedley-Stevenson (MCHPC@SC, 2020)

Tracking Performance Portability on the Yellow Brick Road to Exascale. - Tom Deakin; Andrei Poenaru; Tom Lin; Simon McIntosh-Smith (P3HPC@SC, 2020)

Interpreting and Visualizing Performance Portability Metrics. - Jason Sewall; S. John Pennycook; Douglas Jacobsen; Tom Deakin; Simon McIntosh-Smith (P3HPC@SC, 2020)

Benchmarking the first generation of production quality Arm-based supercomputers. - Simon McIntosh-Smith; James Price; Andrei Poenaru; Tom Deakin (Concurr. Comput. Pract. Exp., 2020)

On measuring the maturity of SYCL implementations by tracking historical performance improvements. - Wei-Chen Lin; Tom Deakin; Simon McIntosh-Smith (IWOCL, 2021)

Analyzing Reduction Abstraction Capabilities. - Tom Deakin; Simon McIntosh-Smith; S. John Pennycook; Jason Sewall (P3HPC@SC, 2021)

Benchmarking and Extending SYCL Hierarchical Parallelism. - Tom Deakin; Simon McIntosh-Smith; Aksel Alpay; Vincent Heuveline (HiPar@SC, 2021)

Navigating Performance, Portability, and Productivity. - S. John Pennycook; Jason D. Sewall; Douglas Jacobsen; Tom Deakin; Simon McIntosh-Smith (Comput. Sci. Eng., 2021)

Heterogeneous Programming for the Homogeneous Majority. - Tom Deakin; James Cownie; Wei-Chen Lin; Simon McIntosh-Smith (P3HPC@SC, 2022)

Benchmarking Fortran DO CONCURRENT on CPUs and GPUs Using BabelStream. - Jeff R. Hammond; Tom Deakin; James Cownie; Simon McIntosh-Smith (PMBS@SC, 2022)

Evaluating ISO C++ Parallel Algorithms on Heterogeneous HPC Systems. - Wei-Chen Lin; Tom Deakin; Simon McIntosh-Smith (PMBS@SC, 2022)

Principles for Automated and Reproducible Benchmarking. - Tuomas Koskela; Ilektra Christidi; Mosè Giordano; Emily Dubrovska; Jamie Quinn; Christopher M. Maynard; Dave Case; Kaan Olgu; Tom Deakin (SC Workshops, 2023)

A Comparison of Mesh-Free Differentiable Programming and Data-Driven Strategies for Optimal Control under PDE Constraints. - Roussel Desmond Nzoyem Ngueguin; David A. W. Barton; Tom Deakin (SC Workshops, 2023)

Mini-Combust - An Open-Source Unstructured FGM Combustion Mini-App for Co-Designing Aero-Engines at Extreme Scale. - Samuel Curtis; Harry Waugh; Tom Deakin; Gihan R. Mudalige (HiPC, 2024)

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)

Efficient Tree-based Parallel Algorithms for N-Body Simulations Using C++ Standard Parallelism. - Thomas Lane Cassell; Tom Deakin; Aksel Alpay; Vincent Heuveline; Gonzalo Brito Gadeschi (SC Workshops, 2024)

A Metric for HPC Programming Model Productivity. - Wei-Chen Lin; Tom Deakin; Simon McIntosh-Smith (SC Workshops, 2024)

AI-Assisted Design-Space Analysis of High-Performance Arm Processors. - Joseph Moore; Tom Deakin; Simon McIntosh-Smith (SC Workshops, 2024)

Assessing the GPU Offload Threshold of GEMM and GEMV Kernels on Modern Heterogeneous HPC Systems. - Finn Wilkinson; Alex Cockrean; Wei-Chen Lin; Simon McIntosh-Smith; Tom Deakin (SC Workshops, 2024)

Preliminary report: Initial evaluation of StdPar implementations on AMD GPUs for HPC. - Wei-Chen Lin; Simon McIntosh-Smith; Tom Deakin (CoRR, 2024)

Neural Context Flows for Learning Generalizable Dynamical Systems. - Roussel Desmond Nzoyem; David A. W. Barton; Tom Deakin (CoRR, 2024)

Extending Contextual Self-Modulation: Meta-Learning Across Modalities, Task Dimensionalities, and Data Regimes. - Roussel Desmond Nzoyem; David A. W. Barton; Tom Deakin (CoRR, 2024)

Neural Context Flows for Meta-Learning of Dynamical Systems. - Roussel Desmond Nzoyem; David A. W. Barton; Tom Deakin (ICLR, 2025)

Towards Foundational Models for Dynamical System Reconstruction: Hierarchical Meta-Learning via Mixture of Experts. - Roussel Desmond Nzoyem; David A. W. Barton; Tom Deakin (CoRR, 2025)

Weight-Space Linear Recurrent Neural Networks. - Roussel Desmond Nzoyem; Nawid Keshtmand; Idriss Tsayem; David A. W. Barton; Tom Deakin (CoRR, 2025)