Bulgarian Project
EPALC: Efficient Parallel Algorithms for Large-Scale Computational Problems
financed by the Bulgarian National Science Fund
(01/2015 - 12/2016)
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Scientific Objectives
- Development and studying of Monte Carlo methods with an improved convergence rate
- Computational geometry of Polynomials
- Development of new efficient tools for sensitivity analysis of large-scale mathematical models
- Implementation and efficiency study of developed algorithms on advanced computing architectures
- Grid infrastructures and High-performance computers
Summary
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.
Work Packages
- 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)
Bulgarian team:
German team:
Bulgarian institutions:
German institutions:
Publications of the Project
Related Projects:
