SkewEngine: enhancing performance of intensive calculations on regular meshes
| dc.centro | E.T.S.I. Informática | es_ES |
| dc.contributor.author | Romero, Felipe | |
| dc.contributor.author | Ortigosa, Pilar M. | |
| dc.contributor.author | Bandera-Burgueño, Gerardo | |
| dc.contributor.author | Romero-Gómez, Luis Felipe | |
| dc.date.accessioned | 2024-03-04T13:33:20Z | |
| dc.date.available | 2024-03-04T13:33:20Z | |
| dc.date.issued | 2024-02-24 | |
| dc.departamento | Arquitectura de Computadores | |
| dc.description.abstract | In various applications such as hyperspectral data manipulation, MRI data exploration, or viewshed identification in digital elevation models, performing arithmetic operations on each point of a data mesh that involves other points can lead to computationally intractable problems. This paper presents SkewEngine, a tool designed to improve the performance of intensive calculations on regular 2-D data meshes, such as images, multispectral data volumes, or digital elevation models. SkewEngine addresses this problem by reorganizing the mesh in memory according to a preferred spatial direction, enabling more efficient execution of intensive calculations. It is demonstrated that SkewEngine offers significant speed improvements for various test cases, suggesting its usefulness in a broader range of applications requiring intensive data processing on regular meshes. | es_ES |
| dc.description.sponsorship | Funding for open access charge: Universidad de Málaga/CBUA. This work has been fnanced by the Spanish Ministry of Science and Technology through the National Plan project PID2022-136575OB-I00, by the Andalusian Government and FEDER funds through the UMA20-FEDERJA-127 project, and by the University of Malaga (PIE22-099). We also thank the Supercomputing and Bioinformatics Service of the University of Malaga and the Spanish Supercomputing Network for facilitating access to the Picasso and Loginexa Supercomputers. | es_ES |
| dc.identifier.citation | Romero, Felipe & Ortigosa, Pilar & Bandera, Gerardo & Romero, Luis. (2023). SkewEngine: Enhancing Performance of Intensive Calculations on Regular Meshes. 10.21203/rs.3.rs-3342748/v1 | es_ES |
| dc.identifier.doi | 10.21203/rs.3.rs-3342748/v1 | |
| dc.identifier.uri | https://hdl.handle.net/10630/30759 | |
| dc.language.iso | eng | es_ES |
| dc.publisher | Springer Nature | es_ES |
| dc.rights | Atribución 4.0 Internacional | * |
| dc.rights.accessRights | open access | es_ES |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
| dc.subject | Informática - Aplicaciones | es_ES |
| dc.subject.other | Hybrid computing | es_ES |
| dc.subject.other | Regular mesh | es_ES |
| dc.subject.other | Memory locality | es_ES |
| dc.title | SkewEngine: enhancing performance of intensive calculations on regular meshes | es_ES |
| dc.type | journal article | es_ES |
| dc.type.hasVersion | VoR | es_ES |
| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | 63245157-a2a2-4980-9f45-a83ac108e7ef | |
| relation.isAuthorOfPublication | 42f0af7a-994e-48e1-b480-e9db8cc83e15 | |
| relation.isAuthorOfPublication.latestForDiscovery | 63245157-a2a2-4980-9f45-a83ac108e7ef |
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