DocumentCode :
3455869
Title :
Scalable parallel implementation of independent components analysis on the graphics processing unit
Author :
Forgette, Jacquelyne ; Smolikova, Renata Wachowiak ; Wachowiak, Mark
Author_Institution :
Dept. of Comput. Sci., Univ. of Western Ontario, London, ON, Canada
fYear :
2011
fDate :
8-11 May 2011
Abstract :
Independent component analysis (ICA) is an important signal processing technique used to extract source signals from signal mixtures. Although useful in a wide range of problems, ICA is computationally expensive, and is therefore not suitable in many real-time or large data size applications. This paper presents a scalable parallel implementation of ICA in which computations are performed on graphics processing units (GPUs). An implementation using the programming toolkit OpenCL, as well as local memory and memory coalescing optimizations, increase ICA efficiency, and potentially improve its utility in data-intensive applications.
Keywords :
blind source separation; graphics processing units; independent component analysis; parallel processing; ICA; data intensive applications; graphic processing unit; independent component analysis; local memory optimization; memory coalescing optimization; programming toolkit OpenCL; scalable parallel implementation; signal mixtures; signal processing technique; source signal extraction; Graphics processing unit; Hardware; Independent component analysis; Kernel; Programming; Real time systems; Signal processing; Graphics processing units; independent component analysis; parallel computing; signal processing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical and Computer Engineering (CCECE), 2011 24th Canadian Conference on
Conference_Location :
Niagara Falls, ON
ISSN :
0840-7789
Print_ISBN :
978-1-4244-9788-1
Electronic_ISBN :
0840-7789
Type :
conf
DOI :
10.1109/CCECE.2011.6030591
Filename :
6030591
Link To Document :
بازگشت