Thinking in Parallel: foreword
[EN] Under the title of Supercomputing Education: Thinking in Parallel, this special issue of the Journal of Supercomputing (SUPE) was promoted from the TEEM'19 International ConferenceFootnote1 held in León (Spain) in October 2019. A special session under the same title was organized at the Co...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2021 |
| País: | España |
| Institución: | Universidad de León |
| Repositorio: | BULERIA. Repositorio Institucional de la Universidad de León |
| OAI Identifier: | oai:buleria.unileon.es:10612/24907 |
| Acceso en línea: | https://link.springer.com/article/10.1007/s11227-021-03848-8 https://hdl.handle.net/10612/24907 |
| Access Level: | acceso abierto |
| Palabra clave: | Informática Ingenierías Robótica 1203.04 Inteligencia Artificial 3311.01 Tecnología de la Automatización 1206.01 Construcción de Algoritmos 1207.03 Cibernética |
| Sumario: | [EN] Under the title of Supercomputing Education: Thinking in Parallel, this special issue of the Journal of Supercomputing (SUPE) was promoted from the TEEM'19 International ConferenceFootnote1 held in León (Spain) in October 2019. A special session under the same title was organized at the Conference, focused on the factors that have to be taken into account for improving training in Supercomputing, on identifying the limitations of Supercomputing training, and on how to provide solutions for these limitations. The use of Supercomputers is wide spreading, constituting an essential component in many fields of science. The interest in the use of high-performance computing (HPC) facilities is also increasing in a growing percentage of undergraduates because the use of these infrastructures allows them to improve their skills and the results of their training. For this reason, the demand of training on supercomputing increases continuously. “Thinking in Parallel” intended to focus on the factors that have to be taking into account for improving training in Supercomputing for improving the performance of researchers and also to try to identify the limitations of current supercomputing training and to provide solutions for these limitations. |
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