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Undergraduate Research Project Management System

Use of Graphical Processor Units to Accelerate Evolutionary Computation for Evolving Image Compression Transforms

Status Current
Seeking Researchers No
Start Date 11/01/2009
End Date 06/30/2010
Funding Source Undergraduate Research Grant
Funding Amount 2,000
Community Partner
Related Course
Last Updated 01/11/2010 11:34PM
Keywords evolutionary computation, image compression, GPU

People

Faculty
  Frank Moore

Student Researchers
  Brendan Babb

Abstract

Image compression is used on a day to day basis by nearly everyone. The JPEG 2000 standard is used to compress images that appear on websites, are stored on digital cameras, are displayed on cell phones, are transmitted by satellites, etc. The JPEG 2000 standard uses a wavelet for compressing and decompressing images. Previous research at UAA has been successful in evolving wavelet-like transforms that improve image compression. This prior research used standalone computers for small, preliminary tests, but required multiple processors on the ARSC supercomputer at UAF in order to complete large scale tests. Evolutionary computation performs similar calculations across many processors; the more processors you have, the faster it works. Graphical Processor Units (GPUs) also have many processors within a single card. Due to widespread use by the multi-billion gaming industry, GPUs have rapidly developed to the point where they are now capable of outperforming supercomputers for numerical calculations, by factors in excess of 100:1. It is now possible to buy a relatively cheap graphics card and insert it into a standard desktop computer to create a personal supercomputer for performing evolutionary computation tasks in significantly less time. The goal of this project is to use GPUs and evolutionary computation to evolve significantly better wavelets for image compression.

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