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@INPROCEEDINGS{Adinets:153430,
author = {Adinets, Andrey and Kraus, Jiri and Axer, Markus and
Huysegoms, Marcel and Köhnen, Stefan and Pleiter, Dirk},
title = {{C}omputation of {M}utual {I}nformation {M}etric for
{I}mage {R}egistration on {M}ultiple {GPU}s},
volume = {8374},
address = {Berlin, Heidelberg},
publisher = {Springer Berlin Heidelberg},
reportid = {FZJ-2014-03047},
isbn = {978-3-642-54419-4 (print)},
series = {Lecture Notes in Computer Science},
pages = {208 - 217},
year = {2014},
comment = {Euro-Par 2013: Parallel Processing Workshops},
booktitle = {Euro-Par 2013: Parallel Processing
Workshops},
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.},
month = {Aug},
date = {2013-08-25},
organization = {Euro-Par 2013: Parallel Processing
Workshops, Aachen (Germany), 25 Aug
2013 - 30 Aug 2013},
cin = {JSC / INM-1},
ddc = {004},
cid = {I:(DE-Juel1)JSC-20090406 / I:(DE-Juel1)INM-1-20090406},
pnm = {41G - Supercomputer Facility (POF2-41G21) / SMHB -
Supercomputing and Modelling for the Human Brain
(HGF-SMHB-2013-2017)},
pid = {G:(DE-HGF)POF2-41G21 / G:(DE-Juel1)HGF-SMHB-2013-2017},
typ = {PUB:(DE-HGF)8 / PUB:(DE-HGF)7},
doi = {10.1007/978-3-642-54420-0_21},
url = {https://juser.fz-juelich.de/record/153430},
}