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The Journal of Supercomputing
Erschienen in: The Journal of Supercomputing 10/2021

01.04.2021

Multidimensional adaptative and deterministic integration in CUDA and OpenMP

verfasst von: R. Quintero-Monsebaiz, A. Meneses-Viveros, F. Carranza, C. G. Cortés, A. González-Zamudio, A. Vela

Erschienen in: The Journal of Supercomputing | Ausgabe 10/2021

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Abstract

Parallelization schemes on many-core architectures, in this case, CUDA and OpenMP, are used to accelerate and improve the accuracy of adaptive multidimensional integration algorithms. The one-dimensional Gauss–Kronrod adaptive method is generalized to 3, 4, 5 and 6 dimensions. The implementation of the traditional tensor product construction of the grid and weights for multidimensional integration is revisited and reformulated taking advantages of the multi and many-core architectures. Tests performed in a set of benchmark functions show that the algorithm is numerically accurate, with accelerations as high as 800X in CUDA and 300X in the OpenMP implementation both compared to a sequential multidimensional integration algorithm.
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Metadaten
Titel
Multidimensional adaptative and deterministic integration in CUDA and OpenMP
verfasst von
R. Quintero-Monsebaiz
A. Meneses-Viveros
F. Carranza
C. G. Cortés
A. González-Zamudio
A. Vela
Publikationsdatum
01.04.2021
Verlag
Springer US
Erschienen in
The Journal of Supercomputing / Ausgabe 10/2021
Print ISSN: 0920-8542
Elektronische ISSN: 1573-0484
DOI
https://doi.org/10.1007/s11227-021-03752-1

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