Skip to content

andronkyr/CUDA---Principal-Direction-Divisive-Partitioning

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

2 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

CUDA - Principal Direction Divisive Partitioning

In this project, an implementation of PDDP algorithm was developed.

The algorithm takes as input a matrix consisting of vectors representing the elements of the data set. The power iteration method is used in order to calculate the output and the final result is a clustering of the input data. The algorithm stops when it has converged.

The implementation in CUDA utilizes shared memory, coalesced accesses in memory as well as atomic operations.

About

An implementation of Principal Direction Divisive Partitioning in CUDA.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published