Detail publikace

GPU Optimization of Convolution for Large 3-D Real Images

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"
}