Name
Abstract | ||
|---|---|---|
The Multi-Level Monte Carlo finite volumes (MLMC-FVM) algorithm was shown to be a robust and fast solver for uncertainty quantification in the solutions of multi-dimensional systems of stochastic conservation laws. A novel load balancing procedure is used to ensure scalability of the MLMC algorithm on massively parallel hardware. We describe this procedure together with other arising challenges in great detail. Finally, numerical experiments in multi-dimensions showing strong and weak scaling of our implementation are presented. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-31464-3_25 | PPAM (1) |
Keywords | Field | DocType |
monte carlo finite volume,numerical experiment,mlmc algorithm,parallel hardware,fast solver,finite volume,static load balancing,stochastic conservation law,novel load,multi-dimensional system,great detail,multi-level monte carlo,conservation laws,linear scaling,uncertainty quantification | Monte Carlo method,Uncertainty quantification,Massively parallel,Load balancing (computing),Computer science,Parallel computing,Hybrid Monte Carlo,Theoretical computer science,Solver,Finite volume method,Monte Carlo molecular modeling | Conference |
Volume | ISSN | Citations |
7203 | 0302-9743 | 7 |
PageRank | References | Authors |
0.60 | 4 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jonas Sukys | 1 | 21 | 3.76 |
| Siddhartha Mishra | 2 | 170 | 21.36 |
| Christoph Schwab | 3 | 595 | 58.38 |