Authors: Gajić, Dušan
Stanković, Radomir 
Radmanović, Miloš
Title: Implementation of dyadic correlation and autocorrelation on graphics processors
Journal: International Journal of Reasoning-based Intelligent Systems
Volume: 4
Issue: 1-2
First page: 82
Last page: 90
Issue Date: 3-Dec-2012
ISSN: 1755-0556
DOI: 10.1504/IJRIS.2012.046495
Abstract: 
The convolution and related operators of correlation and autocorrelation are essential and powerful mathematical tools in machine learning, signal processing, systems theory, and related areas. In particular, representation and handling of systems with binary encoded input and output signals requires intensive computation of the correlation and autocorrelation functions which are defined on the finite dyadic groups as the underlying algebraic structure. This paper presents methods for computing the dyadic correlation and autocorrelation functions on graphics processing units (GPUs). The proposed algorithms are based on the convolution and the Wiener- Khinchin theorems and implemented using the Open Computing Language (OpenCL). We address several key issues in developing an efficient mapping of the computations to the GPU architecture. The experimental results confirm that the application of the proposed method leads to significant computational speedups over traditional C/C++ implementations processed on central processing units (CPUs).
Keywords: Convolution theorem | Dyadic autocorrelation | Dyadic correlation | Fast Walsh transform | General-purpose computing on graphics processing units | GPGPU | GPU computing | OpenCL | Wiener-Khinchin theorem
Publisher: Inderscience

Show full item record

SCOPUSTM   
Citations

1
checked on Apr 22, 2024

Page view(s)

35
checked on Apr 23, 2024

Google ScholarTM

Check

Altmetric

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.