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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Vydáno v:	Computational and mathematical methods Ročník 2; číslo 1
Hlavní autoři:	Rico‐Gallego, Juan A., Díaz‐Martín, Juan C., Moreno‐Álvarez, Sergio, Calvo‐Jurado, Carmen, García‐Zapata, Juan L.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Hoboken John Wiley & Sons, Inc 01.01.2020
Témata:	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
On-line přístup:	Získat plný text
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