Code
05Y00308
Duration
01 March 2008 → 31 December 2012
Funding
Ghent University funding
Promotor
Research disciplines
-
Natural sciences
- Applied mathematics in specific fields
- Artificial intelligence
- Computer architecture and networks
- Distributed computing
- Information sciences
- Information systems
- Programming languages
- Scientific computing
- Theoretical computer science
- Visual computing
- Other information and computing sciences
-
Social sciences
- Cognitive science and intelligent systems
Keywords
machine learning
meta-models
pro-active scheduling
statistical modelling
distibuted computing
Project description
During the design of complex systems (micro-electronics, MEMS, …) simplified 'meta-models' are often used to achieve tractability of analyses. These scalable meta-models are based on a limited number of detailed computer simulations. This project aims at developing new machine learning techniques for generating scalable meta-models in distributed computing environments (e.g. computer clusters and grids).