David Beckingsale
Zitiert von
Zitiert von
RAJA: Portable performance for large-scale scientific applications
DA Beckingsale, J Burmark, R Hornung, H Jones, W Killian, AJ Kunen, ...
2019 ieee/acm international workshop on performance, portability and …, 2019
Caliper: performance introspection for HPC software stacks
D Boehme, T Gamblin, D Beckingsale, PT Bremer, A Gimenez, ...
SC'16: Proceedings of the International Conference for High Performance …, 2016
Accelerating hydrocodes with OpenACC, OpeCL and CUDA
JA Herdman, WP Gaudin, S McIntosh-Smith, M Boulton, DA Beckingsale, ...
3rd International Workshop on Performance Modeling, Benchmarking and …, 2012
CloverLeaf: Preparing hydrodynamics codes for Exascale
AC Mallinson, DA Beckingsale, WP Gaudin, JA Herdman, JM Levesque, ...
Cray User Group (CUG), 2013
Fast multi-parameter performance modeling
A Calotoiu, D Beckinsale, CW Earl, T Hoefler, I Karlin, M Schulz, F Wolf
2016 IEEE International Conference on Cluster Computing (CLUSTER), 172-181, 2016
Umpire: Application-focused management and coordination of complex hierarchical memory
DA Beckingsale, MJ McFadden, JPS Dahm, R Pankajakshan, ...
IBM Journal of Research and Development 64 (3/4), 00: 1-00: 10, 2019
Performance portable C++ programming with RAJA
D Beckingsale, R Hornung, T Scogland, A Vargas
Proceedings of the 24th Symposium on Principles and Practice of Parallel …, 2019
Apollo: Reusable models for fast, dynamic tuning of input-dependent code
D Beckingsale, O Pearce, I Laguna, T Gamblin
2017 IEEE International Parallel and Distributed Processing Symposium (IPDPS …, 2017
Achieving portability and performance through OpenACC
JA Herdman, WP Gaudin, O Perks, DA Beckingsale, AC Mallinson, ...
1st Workshop on Accelerator Programming using Directives, 19-26, 2014
TeaLeaf: A mini-application to enable design-space explorations for iterative sparse linear solvers
S McIntosh-Smith, M Martineau, T Deakin, G Pawelczak, W Gaudin, ...
2017 IEEE International Conference on Cluster Computing (CLUSTER), 842-849, 2017
Resident Block-Structured Adaptive Mesh Refinement on Thousands of Graphics Processing Units
DA Beckingsale, W Gaudin, A Herdman, S Jarvis
44th International Conference on Parallel Processing (ICPP), 61-70, 2015
Towards Portable Performance for Explicit Hydrodynamics Codes
AC Mallinson, DA Beckingsale, WP Gaudin, JA Herdman, SA Jarvis
1st International Workshop on OpenCL (IWOCL), 2013
Artemis: automatic runtime tuning of parallel execution parameters using machine learning
C Wood, G Georgakoudis, D Beckingsale, D Poliakoff, A Gimenez, K Huck, ...
High Performance Computing: 36th International Conference, ISC High …, 2021
A Performance Evaluation of Kokkos & RAJA using the TeaLeaf Mini-App
M Martineau, S McIntosh-Smith, M Boulton, W Gaudin, DA Beckingsale
Optimising Hydrodynamics applications for the Cray XC30 with the application tool suite
W Gaudin, A Mallinson, O Perks, J Herdman, DA Beckingsale, ...
Cray User Group (CUG), 4-8, 2014
Accelerating hydrocodes with OpenACC, OpenCL and CUDA. In 2012 SC Companion: High Performance Computing, Networking Storage and Analysis
JA Herdman, WP Gaudin, S McIntosh-Smith, M Boulton, DA Beckingsale, ...
IEEE, 2012
Funcytuner: Auto-tuning scientific applications with per-loop compilation
T Wang, N Jain, D Beckingsale, D Boehme, F Mueller, T Gamblin
Proceedings of the 48th International Conference on Parallel Processing, 1-10, 2019
Flexible data aggregation for performance profiling
D Böehme, D Beckingsale, M Schulz
2017 IEEE International Conference on Cluster Computing (CLUSTER), 419-428, 2017
Towards Automated Memory Model Generation via Event Tracing
OFJ Perks, DA Beckingsale, SD Hammond, I Miller, JA Herdman, ...
The Computer Journal 56 (2), 156-174, 2013
Performance modelling of magnetohydrodynamics codes
RF Bird, SA Wright, DA Beckingsale, SA Jarvis
Computer Performance Engineering 7587, 197-209, 2013
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