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Computational Performance Improvement of Steganography Using GPU

Amol H. Jaikar, V. H. Joshi

Abstract


Today Graphical Processing Unit (GPU) is used for other Applications also, because of its High Computational Power and Memory Bandwidth. Many of the Applications, they are using GPU for improving their Performance. (E.g. scientific applications).
We are using this Computational Power for our Application. We take a first step towards validating this hypothesis, focusing on Steganograph. We are trying to improve the speed of computation in the process of Steganography, using parallel execution of threads. This paper explains parallel programming on GPU.
GPU is having one more advantage that it can run many threads parallel at a time. Using this developer can make Multithreaded Application.
Parallel programming will become important part of the computer industry because now these days the entire desktops are having minimum dual core processors instead of single core. Hardware is improving their performance by using Moor’s law but Software Applications are not developing with the consideration of Hardware capabilities.


Keywords


Graphical Processing Unit (GPU), Steganoghraphy, Compute Unified Device Architecture (CUDA), Parallel processing, Image processing, Grid computing, bmp file format.

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References


CUDA programming model. http://developer.nvidia.com.

Geforce 8 Series, http://www.nvidia.com/

NVIDIA CUDA Compute Unified Device Architecture http://www.nvidia.com/cuda

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Owens, J.D., et al., A Survey of General-Purpose Computation on Graphics Hardware. Computer Graphics Forum, 2007.

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Exploiting Graphics Processing Units to Accelerate Distributed Storage Systems

http://local.wasp.uwa.edu.au/%7Epbourke/dataformats/bmp/

http://atlc.sourceforge.net/bmp.html

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AES encryption on GPU ww.manavski.com/downloads/PID505889.pdf

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http://en.wikipedia.org/wiki/Steganography

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