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The goal of this course is to utilize the supercomputing power of programmable PC graphics cards (Graphics Processing Units-GPUs) for scientific, entertainment, and management applications. The topics for class projects includes the following:
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The goal of this course is to utilize the supercomputing power of programmable PC graphics cards (Graphics Processing Units-GPUs) for scientific, entertainment, and management applications.  
  
:Data prepresentation methods
+
The topics for class projects includes the following:  
 +
 
 +
*<B>Data prepresentation methods</B>
 
::Sparse matrix representation and multiplication  
 
::Sparse matrix representation and multiplication  
:Data Analysis algorithms  
+
*<B>Data Analysis algorithms</B>
 
::Kernel Density Estimation algorithm  
 
::Kernel Density Estimation algorithm  
 
::Distance map generation algorithm  
 
::Distance map generation algorithm  

Latest revision as of 11:37, 30 November 2009

The goal of this course is to utilize the supercomputing power of programmable PC graphics cards (Graphics Processing Units-GPUs) for scientific, entertainment, and management applications.

The topics for class projects includes the following:

  • Data prepresentation methods
Sparse matrix representation and multiplication
  • Data Analysis algorithms
Kernel Density Estimation algorithm
Distance map generation algorithm
Difference of Gaussian algorithm
Likelyhood ratio test algorithm

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