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KARAS, P. SVOBODA, D. ZEMČÍK, P.
Originální název
GPU Optimization of Convolution for Large 3-D Real Images
Typ
článek ve sborníku mimo WoS a Scopus
Jazyk
angličtina
Originální abstrakt
In this paper, we propose a method for computing convolution of large 3-D images with respect to real signals. The convolution is performed in a frequency domain using a convolution theorem. Due to properties of real signals, the algorithm can be optimized so that both time and the memory consumption are halved when compared to complex signals of the same size. Convolution is decomposed in a frequency domain using the decimation in frequency (DIF) algorithm. The algorithm is accelerated on a graphics hardware by means of the CUDA parallel computing model, achieving up to 10x speedup with a single GPU over an optimized implementation on a quad-core CPU.
Klíčová slova
gpu, convolution, 3-D, image processing
Autoři
KARAS, P.; SVOBODA, D.; ZEMČÍK, P.
Rok RIV
2012
Vydáno
4. 9. 2012
Nakladatel
Springer Verlag
Místo
Heidelberg
ISBN
978-3-642-33139-8
Kniha
Proceedings of ACVIS 2012
Strany od
59
Strany do
71
Strany počet
13
BibTex
@inproceedings{BUT97536, author="Pavel {Karas} and David {Svoboda} and Pavel {Zemčík}", title="GPU Optimization of Convolution for Large 3-D Real Images", booktitle="Proceedings of ACVIS 2012", year="2012", pages="59--71", publisher="Springer Verlag", address="Heidelberg", doi="10.1007/978-3-642-33140-4\{_}6", isbn="978-3-642-33139-8" }