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Publication Detail
Improved CUDA 3D Medical Image Registration
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Publication Type:Other
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Authors:Langdon WB
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Publication date:2014
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Editors:Giles M,Kelly P,McIntosh-Smith S,Pullan G,Spiga F,Thomas D
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Addresses:Cambridge
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Notes:keywords: genetic algorithms, genetic programming, SBSE, GPGPU, NiftyReg size: 1 page notes: http://www.many-core.group.cam.ac.uk/ukmac2014/ One page summary of \citeLangdon:2014:GECCO but emphasis on result rather than GP.
Abstract
A combination of manual and genetic improvement (GI) can optimise a critical component of NiftyReg healthcare industry software across a diverse range of six nVidia graphics processing units (GPUs). The improved K20c kernel gives a speed up >2000 fold compared to released code on a 3GHz CPU
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