Performance Analysis of Sobel Edge Detection Filter on GPU using CUDA & OpenGL
Computer Engineering Department, VIER-kotambi, INDIA
International Journal for Research in Applied Science and Engineering Technology (IJRASET), Vol. 1, Issue III, 2013
@article{shah2013performance,
title={Performance Analysis of Sobel Edge Detection Filter on GPU using CUDA & OpenGL},
author={Shah, Ms Khyati},
year={2013}
}
CUDA(Compute Unified Device Architecture) is a novel technology of general-purpose computing on the GPU, which makes users develop general GPU (Graphics Processing Unit) programs easily. GPUs are emerging as platform of choice for Parallel High Performance Computing. GPUs are good at data intensive parallel processing with availability of software development platforms such as CUDA (developed by Nvidia for its Geforce series GPUs). Basic goal of CUDA is to help programmers focus on the task of parallelization of the algorithms rather than spending time on their implementation. It supports the Heterogeneous computation where applications use both the CPU and GPU. In this paper we propose the implementation of sobel edge detection filter on GeForce GT 130 on MAC OS using CUDA and OpenGL. We reduces the Global Memory using kernel function. Also compare their results and performance to the previous implementation and it gives the more optimized results.
November 10, 2013 by hgpu
