Exploiting nested task-parallelism in the H-LU factorization
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Exploiting nested task-parallelism in the H-LU factorizationAutoria
Data de publicació
2019-04Editor
ElsevierCita bibliogràfica
CARRATALÁ-SÁEZ, Rocío, et al. Exploiting Nested Task-Parallelism in the H-LU Factorization. Journal of Computational Science, 2019, 33:20-33Tipus de document
info:eu-repo/semantics/articleVersió de l'editorial
https://www.sciencedirect.com/science/article/pii/S1877750318301352Versió
info:eu-repo/semantics/submittedVersionParaules clau / Matèries
Resum
We address the parallelization of the LU factorization of hierarchical matrices (-matrices) arising from boundary element methods. Our approach exploits task-parallelism via the OmpSs programming model and runtime, ... [+]
We address the parallelization of the LU factorization of hierarchical matrices (-matrices) arising from boundary element methods. Our approach exploits task-parallelism via the OmpSs programming model and runtime, which discovers the data-flow parallelism intrinsic to the operation at execution time, via the analysis of data dependencies based on the memory addresses of the tasks’ operands. This is especially challenging for H-matrices, as the structures containing the data vary in dimension during the execution. We tackle this issue by decoupling the data structure from that used to detect dependencies. Furthermore, we leverage the support for weak operands and early release of dependencies, recently introduced in OmpSs-2, to accelerate the execution of parallel codes with nested task-parallelism and fine-grain tasks. As a result, we obtain a significant improvement in the parallel performance with respect to our previous work. [-]
Proyecto de investigación
MINECO (CICYT TIN2014-53495-R) ; FEDER (TIN2017-82972-R) ; Universitat Jaume I (UJI-B2017-46); MECD (FPU program)Drets d'accés
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