An early evaluation of intel's optane dc persistent memory module and its impact on high-performance scientific applications M Weiland, H Brunst, T Quintino, N Johnson, O Iffrig, S Smart, C Herold, ... Proceedings of the international conference for high performance computing …, 2019 | 82 | 2019 |
A highly scalable Met Office NERC Cloud model N Brown, M Weiland, A Hill, B Shipway, C Maynard, T Allen, M Rezny arXiv preprint arXiv:2009.12849, 2020 | 54 | 2020 |
Chapel, Fortress and X10: novel languages for HPC M Weiland EPCC, The University of Edinburgh, Tech. Rep. HPCxTR0706 1, 15-16, 2007 | 54 | 2007 |
Developing a scalable hybrid MPI/OpenMP unstructured finite element model X Guo, M Lange, G Gorman, L Mitchell, M Weiland Computers & Fluids 110, 227-234, 2015 | 48 | 2015 |
Achieving efficient strong scaling with PETSc using hybrid MPI/OpenMP optimisation M Lange, G Gorman, M Weiland, L Mitchell, J Southern Supercomputing: 28th International Supercomputing Conference, ISC 2013 …, 2013 | 27 | 2013 |
Investigating applications on the A64FX A Jackson, M Weiland, N Brown, A Turner, M Parsons 2020 IEEE International Conference on Cluster Computing (CLUSTER), 549-558, 2020 | 26 | 2020 |
Learning musical pitch structures with hierarchical hidden Markov models M Weiland, A Smaill, P Nelson Journees d’Informatique Musical, 2005 | 25 | 2005 |
Evaluating the arm ecosystem for high performance computing A Jackson, A Turner, M Weiland, N Johnson, O Perks, M Parsons Proceedings of the Platform for Advanced Scientific Computing Conference, 1-11, 2019 | 21 | 2019 |
In situ data analytics for highly scalable cloud modelling on Cray machines N Brown, M Weiland, A Hill, B Shipway Concurrency and Computation: Practice and Experience 30 (1), e4331, 2018 | 18 | 2018 |
Exploiting the performance benefits of storage class memory for HPC and HPDA workflows M Weiland, A Jackson, N Johnson, M Parsons Supercomputing Frontiers and Innovations 5 (1), 79-94, 2018 | 12 | 2018 |
A directive based hybrid met office nerc cloud model N Brown, A Lepper, M Weiland, A Hill, B Shipway, C Maynard Proceedings of the Second Workshop on Accelerator Programming using …, 2015 | 10 | 2015 |
Performance evaluation of adaptive routing on dragonfly-based production systems S Chunduri, K Harms, T Groves, P Mendygral, J Zarins, M Weiland, ... 2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS …, 2021 | 8 | 2021 |
Mixed-mode implementation of PETSc for scalable linear algebra on multi-core processors M Weiland, L Mitchell, G Gorman, S Kramer, M Parsons, J Southern arXiv preprint arXiv:1205.2005, 2012 | 7 | 2012 |
Benchmarking for power consumption monitoring: Description of benchmarks designed to expose power usage characteristics of parallel hardware systems, and preliminary results M Weiland, N Johnson Computer Science-Research and Development 30 (2), 155-163, 2015 | 6 | 2015 |
Exploring the thread-level parallelisms for the next generation geophysical fluid modelling framework Fluidity-ICOM X Guo, G Gorman, M Lange, L Mitchell, M Weiland Procedia Engineering 61, 251-257, 2013 | 6 | 2013 |
Exploiting dynamic sparse matrices for performance portable linear algebra operations C Stylianou, M Weiland 2022 IEEE/ACM International Workshop on Performance, Portability and …, 2022 | 5 | 2022 |
Usage scenarios for byte-addressable persistent memory in high-performance and data intensive computing M Weiland, B Homölle Journal of Computer Science and Technology 36, 110-122, 2021 | 5 | 2021 |
Progressive load balancing of asynchronous algorithms J Zarins, M Weiland Proceedings of the Seventh Workshop on Irregular Applications: Architectures …, 2017 | 5 | 2017 |
Chapel, Fortress and X10: novel languages for HPC. EPCC, The University of Edinburgh M Weiland Tech. Rep. HPCxTR0706, 2007 | 5 | 2007 |
An architecture for high performance computing and data systems using byte-addressable persistent memory A Jackson, M Weiland, M Parsons, B Homölle High Performance Computing: ISC High Performance 2019 International …, 2019 | 4 | 2019 |