Parallel Performance of GTM Dimension Reduction
Project Information
- Discipline
- Computer Science (401)
- Orientation
- Research
Research on Parallel Performance of GTM Dimension Reduction
Intellectual MeritPerformance study of parallel GTM algorithm is important to process large scale data for data mining.
Broader ImpactsGTM 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)
Research for Parallel Performance of GTM Dimension Reduction
Scale of UseIf 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