Applications of Heterogeneous Computing in Computational and Simulation Science

As the size and complexity of scientific problems and datasets grow, scientists from a broad range of discipline areas are relying more and more on computational methods and simulations to help solve their problems. This paper presents a summary of heterogeneous algorithms and applications that have...

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Bibliographic Details
Published in2011 Fourth IEEE International Conference on Utility and Cloud Computing pp. 382 - 389
Main Authors Domanski, L., Bednarz, T., Gureyev, T. E., Murray, L., Huang, E., Taylor, J. A.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2011
Subjects
Clustering algorithms
Computational modeling
Equations
Genetics
GPU clusters
GPUs
Graphics processing unit
heterogeneous computing
high performance computing
Mathematical model
Servers
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Summary:As the size and complexity of scientific problems and datasets grow, scientists from a broad range of discipline areas are relying more and more on computational methods and simulations to help solve their problems. This paper presents a summary of heterogeneous algorithms and applications that have been developed by a large research organization (CSIRO) for solving practical and challenging science problems faster than is possible with conventional multi-core CPUs alone. The problem domains discussed include biological image analysis, computed tomography reconstruction, marine biogeochemical models, fluid dynamics, and bioinformatics. The algorithms utilize GPUs and multi-core CPUs on a scale ranging from single workstation installations through to large GPU clusters. Results demonstrate that large GPU clusters can be used to accelerate a variety of practical science applications, and justify the significant financial investment and interest being placed into such systems.
ISBN:1457721163
9781457721168
DOI:10.1109/UCC.2011.64