Publication details

Deconvolution of huge 3-D images: Parallelization strategies on a multi-GPU system

Authors

KARAS Pavel KUDERJAVÝ Michal SVOBODA David

Year of publication 2013
Type Article in Proceedings
Conference Algorithms and Architectures for Parallel Processing
MU Faculty or unit

Faculty of Informatics

Citation
Web http://dx.doi.org/10.1007/978-3-319-03859-9_24
Doi http://dx.doi.org/10.1007/978-3-319-03859-9_24
Field Informatics
Keywords deconvolution; gpu; multi-gpu; parallelization; implementation; algorithm; em-mle; richardson-lucy; ictm; wiener
Description In this paper, we discuss strategies to parallelize selected deconvolution methods on a multi-GPU system. We provide a comparison of several approaches to split the deconvolution into subtasks while keeping the amount of costly data transfers as low as possible, and propose own implementation of three deconvolution methods which achieves up to 65x speedup over the CPU one. In the experimental part, we analyse how the individual stages of the computation contribute to the overall computation time as well as how the multi-GPU implementation scales in various setups. Finally, we identify bottlenecks of the system.
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