Workload Balancing on Heterogeneous Systems: A Case Study of Sparse Grid Interpolation

Alin Muraraşu, Josef Weidendorfer, Arndt Bode

Research output: Chapter in Book/Report/Conference proceedingChapter

3 Scopus citations


Multi-core parallelism and accelerators are becoming common features of today’s computer systems, as they allow for computational power without sacrificing energy efficiency. Due to heterogeneity, tuning for each type of compute unit and adequate load balancing is essential. This paper proposes static and dynamic solutions for load balancing in the context of an application for visualizing high-dimensional simulation data. The application relies on the sparse grid technique for data compression. Its performance critical part is the interpolation routine used for decompression. Results show that our load balancing scheme allows for an efficient acceleration of interpolation on heterogeneous systems containing multi-core CPUs and GPUs.
Original languageEnglish (US)
Title of host publicationEuro-Par 2011: Parallel Processing Workshops
PublisherSpringer Nature
Number of pages10
ISBN (Print)9783642297397
StatePublished - 2012
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): UK-C0020
Acknowledgements: This publication is based on work supported by AwardNo. UK-C0020, made by King Abdullah University of Science and Technology(KAUST).
This publication acknowledges KAUST support, but has no KAUST affiliated authors.


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