Computation of Mutual Information Metric for Image Registration on Multiple GPUs

Adinets, Andrey; Axer, Markus; Köhnen, Stefan; Huysegoms, Marcel; Pleiter, Dirk; Kraus, Jiri

doi:10.1007/978-3-642-54420-0_21

Contribution to a conference proceedings/Contribution to a book

FZJ-2014-03047

Computation of Mutual Information Metric for Image Registration on Multiple GPUs

Adinets, A. (Corresponding Author)FZJ* ; Kraus, J. ; Axer, M.FZJ* ; Huysegoms, M.FZJ* ; Köhnen, S.FZJ* ; Pleiter, D.FZJ*

2014
Springer Berlin Heidelberg Berlin, Heidelberg
ISBN: 978-3-642-54419-4 (print), 978-3-642-54420-0 (electronic)

Euro-Par 2013: Parallel Processing Workshops
Euro-Par 2013: Parallel Processing Workshops, Aachen, Germany, 25 Aug 2013 - 30 Aug 2013 Berlin, Heidelberg : Springer Berlin Heidelberg, Lecture Notes in Computer Science 8374, 208 - 217 (2014) [10.1007/978-3-642-54420-0_21]

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Please use a persistent id in citations: doi:10.1007/978-3-642-54420-0_21

Abstract: Because of their computational power, GPUs are widely used in the field of image processing. Registration of brain images has already been successfully accelerated with GPUs, but registration of high-resolution human brain images presents new challenges due to large amounts of data and images not fitting in the memory of a single device.In this paper, we address this issue with two approaches. The first approach replicates image data in system memory of each node and distributes only a part of the data over multiple GPUs. The second approach splits image data between multiple GPUs, and overlaps computation and communication to hide latency. For both approaches, we present a performance analysis and comparison.

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