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...

Celý popis

Podrobná bibliografia

Vydané v:	Computational and mathematical methods Ročník 2; číslo 1
Hlavní autori:	Rico‐Gallego, Juan A., Díaz‐Martín, Juan C., Moreno‐Álvarez, Sergio, Calvo‐Jurado, Carmen, García‐Zapata, Juan L.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Hoboken John Wiley & Sons, Inc 01.01.2020
Predmet:	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 prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!