Performance evaluation of model‐driven partitioning algorithms for data‐parallel kernels on heterogeneous platforms-Reference-Cited by-同舟云学术

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

Published:2019-03-31 Issue:1 Volume:2 Page:
ISSN:2577-7408
Container-title:Computational and Mathematical Methods
language:en
Short-container-title:Comp and Math Methods

Author:

Rico‐Gallego Juan A.¹^ORCID,Díaz‐Martín Juan C.²^ORCID,Moreno‐Álvarez Sergio¹,Calvo‐Jurado Carmen³^ORCID,García‐Zapata Juan L.³

Affiliation:

1. Department of Computer Systems Engineering and Telematics University of Extremadura Cáceres Spain

2. Department of Computer Technology and Communications University of Extremadura Cáceres Spain

3. Department of Mathematics University of Extremadura Cáceres Spain

Funder

European Regional Development Fund

Publisher

Wiley

Subject

Computational Mathematics,Computational Theory and Mathematics,Computational Mechanics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cmm4.1017

Reference15 articles.

1. Matrix multiplication on heterogeneous platforms

2. FuPerMod: a software tool for the optimization of data-parallel applications on heterogeneous platforms

3. AlexandrovA IonescuMF SchauserKE ScheimanC.LogGP: Incorporating Long Messages into the LogP Model ‐ One Step Closer Towards a Realistic Model for Parallel Computation.Santa Barbara CA:University of California at Santa Barbara;1995.

4. KielmannT BalHE VerstoepK.Fast measurement of LogP parameters for message passing platforms. In: Rolim J ed.Parallel and Distributed Processing. IPDPS 2000. Lecture Notes in Computer Science. Vol. 1800.Berlin Germany:Springer;2000:1176‐1183.

5. A Parallel Computational Model for Heterogeneous Clusters

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