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...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	Computational and mathematical methods Jg. 2; H. 1
Hauptverfasser:	Rico‐Gallego, Juan A., Díaz‐Martín, Juan C., Moreno‐Álvarez, Sergio, Calvo‐Jurado, Carmen, García‐Zapata, Juan L.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Hoboken John Wiley & Sons, Inc 01.01.2020
Schlagworte:	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-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!