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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 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 | ||
− | + | *<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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