Workload Balancing on Heterogeneous Systems: A Case Study of Sparse Grid Interpolation
KAUST Grant NumberUK-C0020
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AbstractMulti-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.
CitationMuraraşu A, Weidendorfer J, Bode A (2012) Workload Balancing on Heterogeneous Systems: A Case Study of Sparse Grid Interpolation. Lecture Notes in Computer Science: 345–354. Available: http://dx.doi.org/10.1007/978-3-642-29740-3_39.
SponsorsThis publication is based on work supported by AwardNo. UK-C0020, made by King Abdullah University of Science and Technology(KAUST).
PublisherSpringer Science + Business Media