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DC Field | Value | Language |
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dc.contributor.author | Santander Jiménez, Sergio | - |
dc.contributor.author | Vega Rodríguez, Miguel Ángel | - |
dc.contributor.author | Sousa, Leonel | - |
dc.date.accessioned | 2022-01-21T09:09:49Z | - |
dc.date.available | 2022-01-21T09:09:49Z | - |
dc.date.issued | 2022 | - |
dc.identifier.uri | http://hdl.handle.net/10662/13450 | - |
dc.description.abstract | Optimization problems are becoming increasingly difficult challenges as a result of the definition of more realistic formulations and the availability of larger input data. Fortunately, the computing capabilities of state-of-the-art heterogeneous systems represent an opportunity to deal with the main complexity factors of these problems. These platforms open the door to the definition of robust metaheuristic solvers, in which parallel computations of different nature can be efficiently mapped to the most suitable architectures and hardware resources. This work investigates the combination of multi-level parallelism and heterogeneous computing to address an important multiobjective problem in bioinformatics: phylogenetics. A parallel metaheuristic approach, based on the joint exploitation of parallel tasks at the algorithm, iteration, and solution levels, is proposed to tackle computationally intensive inferences on CPU+GPU systems. Different heterogeneous design alternatives are also discussed, in accordance with the way the interactions between CPU and GPU are handled. The experimental evaluation of the proposal on real-world biological datasets points out the benefits of using multi-level, heterogeneous strategies, reporting accelerations up to 396x over the baseline metaheuristic as well as significant energy savings with regard to other parallel approaches, without impacting multiobjective solution quality. | es_ES |
dc.description.sponsorship | This work was partially funded by the MCIU (Ministry of Science, Innovation and Universities, Spain), the AEI (State Research Agency, Spain), and the ERDF (European Regional Development Fund, EU), under the contract PID2019-107299GBI00/AEI/10.13039/501100011033 (Multi-HPC-Bio project), as well as Portuguese funds through FCT (Fundação para a Ciência e a Tecnologia, Portugal) projects UIDB/50021/2020 and LISBOA-01-0145-FEDER-031901 (PTDC/CCI-COM/31901/2017, HiPErBio). | es_ES |
dc.format.extent | 17 p. | es_ES |
dc.format.mimetype | application/pdf | en_US |
dc.language.iso | eng | es_ES |
dc.publisher | Elsevier | es_ES |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Evolutionary computation | es_ES |
dc.subject | Bioinformatics | es_ES |
dc.subject | Multi-level parallelism | es_ES |
dc.subject | Heterogeneous computing | es_ES |
dc.subject | High performance computing | es_ES |
dc.subject | Computación heterogénea | es_ES |
dc.subject | Paralelismo multinivel | es_ES |
dc.subject | Computación evolutiva | es_ES |
dc.subject | Computación de alto rendimiento | es_ES |
dc.subject | Bioinformática | es_ES |
dc.title | Exploiting multi-level parallel metaheuristics and heterogeneous computing to boost phylogenetics | es_ES |
dc.type | article | es_ES |
dc.description.version | peerReviewed | es_ES |
europeana.type | TEXT | en_US |
dc.rights.accessRights | openAccess | es_ES |
dc.subject.unesco | 1203 Ciencias de los Ordenadores | - |
dc.subject.unesco | 3304 Tecnología de Los Ordenadores | - |
europeana.dataProvider | Universidad de Extremadura. España | es_ES |
dc.identifier.bibliographicCitation | Santander Jiménez, S., Vega Rodríguez, M.A., Sousa, L. (2022). Exploiting multi-level parallel metaheuristics and heterogeneous computing to boost phylogenetics. Future Generation Computer Systems, 127, 208-224. https://doi.org/10.1016/j.future.2021.09.011 | es_ES |
dc.type.version | publishedVersion | es_ES |
dc.contributor.affiliation | Instituto de Engenharia de Sistemas e Computadores - Investigação e Desenvolvimento em Lisboa (INESC-ID). Portugal | es_ES |
dc.contributor.affiliation | Universidad de Extremadura. Departamento de Tecnología de los Computadores y de las Comunicaciones | es_ES |
dc.identifier.doi | 10.1016/j.future.2021.09.011 | - |
dc.identifier.publicationtitle | Future Generation Computer Systems | es_ES |
dc.identifier.publicationfirstpage | 208 | es_ES |
dc.identifier.publicationlastpage | 224 | es_ES |
dc.identifier.publicationvolume | 127 | es_ES |
dc.identifier.e-issn | 0167-739X | - |
Appears in Collections: | DTCYC - Artículos |
Files in This Item:
File | Description | Size | Format | |
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j.future.2021.09.011.pdf | 2,38 MB | Adobe PDF | View/Open |
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