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Performance and irregular behavior of adaptive task partitioning

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2001) 2074 118-127
DOI: 10.1007/3-540-45718-6_14
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Abstract

We study the effect of irregular function behavior and dynamic task partitioning on the parallel performance of the adaptive multivariate integration algorithm currently incorporated in ParInt. In view of the implicit hot spots in the computations, load balancing is essential to maintain parallel efficiency. A convergence model is given for a class of singular functions. Results are included for the computation of the cross section of a particle interaction. The adaptive meshes produced by ParInt for these problems are represented using the ParVis visualization tool.

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APA

de Doncker, E., Zanny, R., Kaugars, K., & Cucos, L. (2001). Performance and irregular behavior of adaptive task partitioning. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2074, pp. 118–127). Springer Verlag. https://doi.org/10.1007/3-540-45718-6_14

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