Parallel Performance of GTM Dimension Reduction

Project Information

Discipline
Computer Science (401) 
Orientation
Research 
Abstract

Research on Parallel Performance of GTM Dimension Reduction

Intellectual Merit

Performance study of parallel GTM algorithm is important to process large scale data for data mining.

Broader Impacts

GTM dimension reduction has many potentials to be used in various fields, including cheminformatics and text mining.

Project Contact

Project Lead
Jong Youl Choi (jychoi) 
Project Manager
Jong Youl Choi (jychoi) 

Resource Requirements

Hardware Systems
  • alamo (Dell optiplex at TACC)
  • hotel (IBM iDataPlex at U Chicago)
  • india (IBM iDataPlex at IU)
  • sierra (IBM iDataPlex at SDSC)
  • xray (Cray XM5 at IU)
  • bravo (large memory machine at IU)
  • delta (GPU Cloud)
 
Use of FutureGrid

Research for Parallel Performance of GTM Dimension Reduction

Scale of Use

If possible, I want to use as many nodes as possible for performance study of Parallel GTM Dimension Reduction

Project Timeline

Submitted
12/08/2010 - 21:25 
»