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oai:riuma.uma.es:10630/307592026-02-03T11:14:19Zcom_10630_2254col_10630_37953

Romero, Felipe Ortigosa, Pilar M. Bandera-Burgueño, Gerardo Romero-Gómez, Luis Felipe 2024-03-04T13:33:20Z 2024-03-04T13:33:20Z 2024-02-24 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 https://hdl.handle.net/10630/30759 10.21203/rs.3.rs-3342748/v1 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. eng http://creativecommons.org/licenses/by/4.0/ open access Atribución 4.0 Internacional Informática - Aplicaciones SkewEngine: enhancing performance of intensive calculations on regular meshes journal article