Efficient Parallel Algorithms for Large-Scale Computational Problems
About the project
This project was submitted for funding from the Bulgarian National Science fund for Financing of Scientific Research in Priority Area Information and Communication technologies including research in the field of mathematics.
The project was officially approved for funding in November 2014 and it will continue for 24 months and focuses on fundamental research. The main objectives of the projects are:
Development and studying of Monte Carlo methods with an improved convergence rate
Implementation and efficiency study of developed algorithms on advanced computing architectures - Grid infrastructures and High-performance computers
Development of new efficient tools for sensitivity analysis of large-scale mathematical models
Computational geometry of Polynomials
Working Packages and their Leaders
The main objective of the project is to develop efficient Monte Carlo methods and parallel implementation tools for large-scale mathematical models. We plan to implement the developed tools to four areas of ground breaking applications: Environmental modeling, Quantum transport in nanostructures, and Optimization of real-live and industrial problems.
The main part of the investigation will be focused on the development of parallel Monte Carlo algorithms with an improved convergence rate for sensitivity analysis. The use of the existing supercomputer IBM BlueGene/P, as well as AComIn, EGEE and SEE-GRID Grid infrastructures is an important condition for the success of the project.
- Advanced Monte Carlo Numerical Methods (Prof. Ivan Dimov)
- Wigner Monte Carlo Approaches for Modeling of Quantum Phenomena (Dr. Jean Michel Sellier)
- Computational Geometry of Polynomials (Acad. Blagovest Sendov)
- Advanced Numerical Methods (Prof. Lubin Valkov)
- Stochastic Algorithms for Optimization Problems (Assoc. Prof. Stefka Fidanova)
- Sensitivity Analysis of Large-scale Environmental Problems (Assoc. Prof. Tzvetan Ostromsky)