Performance evaluation of model‐driven partitioning algorithms for data‐parallel kernels on heterogeneous platforms

Data‐ parallel applications running on heterogeneous high‐performance computing platforms require a nonuniform distribution of the workload between available processes. Data partitioning algorithms are formulated as an optimization problem. Departing from the computational performance models of the...

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Bibliographic Details

Published in:	Computational and mathematical methods Vol. 2; no. 1
Main Authors:	Rico‐Gallego, Juan A., Díaz‐Martín, Juan C., Moreno‐Álvarez, Sergio, Calvo‐Jurado, Carmen, García‐Zapata, Juan L.
Format:	Journal Article
Language:	English
Published:	Hoboken John Wiley & Sons, Inc 01.01.2020
Subjects:	Algorithms Communication communication optimization communication performance models Cost analysis data‐parallel kernels heterogeneous platforms Kernels Mathematical models Optimization Partitioning partitioning algorithms Performance enhancement Performance evaluation Workload
ISSN:	2577-7408, 2577-7408
Online Access:	Get full text
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