Acceleration of image blurring algorithm on multicore architecture

Author

Arora, Aman ; Pande, N.A.

Author_Institution

Electron. & Telecommun. Eng., S.R.P.C.E., Nagpur, India

fYear

2014

Firstpage

1

Lastpage

4

Abstract

Production chains featuring industrial vision are becoming more and more widespread. Those processes are often heavy and applied to high definition images with important frame rate. Powerful calculators are thus needed to follow the ever growing production rate. NVIDIA is currently designing interfaces providing a CUDA (Compute Unified Device Architecture) architecture allowing parallel data computation. This could increase the performance of every operating system using graphical processing units (GPU). Pure Data, thanks to its graphical modular development environment, allows fast prototype developments. Those factors led us to start a research program dedicated to the realizations of image processing modules for Pure Data written in CUDA. So in this we have implemented image blurring algorithm to get familiar with GPGPU.

Keywords

graphics processing units; image restoration; multiprocessing systems; parallel architectures; CUDA architecture; GPGPU; GPU; NVIDIA; compute unified device architecture; graphical modular development environment; graphical processing units; image blurring algorithm; industrial vision; multicore architecture; parallel data computation; production chains; Central Processing Unit; Computer architecture; Convergence; Graphics processing units; Image processing; Instruction sets; Programming; Algorithm; CUDA; GPGPU (General Purpose Computing using Graphics Processing Unit); Image Processing; Optimization;

fLanguage

English

Publisher

ieee

Conference_Titel

Convergence of Technology (I2CT), 2014 International Conference for

Print_ISBN

978-1-4799-3758-5

Type

conf

DOI

10.1109/I2CT.2014.7092182

Filename

7092182