Pre-exascale HPC approaches for molecular dynamics simulations. Covid-19 research: A use case
Exascale computing has been a dream for ages and is close to becoming a reality that will impact how molecular simulations are being performed, as well as the quantity and quality of the information derived for them. We review how the biomolecular simulations field is anticipating these new architec...
| Autores: | , , , , , , , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2022 |
| País: | España |
| Institución: | Universidad de Barcelona |
| Repositorio: | Dipòsit Digital de la UB |
| OAI Identifier: | oai:diposit.ub.edu:2445/187361 |
| Acceso en línea: | https://hdl.handle.net/2445/187361 |
| Access Level: | acceso abierto |
| Palabra clave: | COVID-19 Models matemàtics Mathematical models |
| Sumario: | Exascale computing has been a dream for ages and is close to becoming a reality that will impact how molecular simulations are being performed, as well as the quantity and quality of the information derived for them. We review how the biomolecular simulations field is anticipating these new architectures, making emphasis on recent work from groups in the BioExcel Center of Excellence for High Performance Computing. We exemplified the power of these simulation strategies with the work done by the HPC simulation community to fight Covid-19 pandemics. This article is categorized under: Data Science > Computer Algorithms and Programming Data Science > Databases and Expert Systems Molecular and Statistical Mechanics > Molecular Dynamics and Monte-Carlo Methods |
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