Scheduling massively parallel multigrid for multilevel Monte Carlo methods

12 Jul 2016 Gmeiner Björn Drzisga Daniel Ruede Ulrich Scheichl Robert Wohlmuth Barbara

The computational complexity of naive, sampling-based uncertainty quantification for 3D partial differential equations is extremely high. Multilevel approaches, such as multilevel Monte Carlo (MLMC), can reduce the complexity significantly, but to exploit them fully in a parallel environment, sophisticated scheduling strategies are needed... (read more)

PDF Abstract
No code implementations yet. Submit your code now

Categories


  • COMPUTATIONAL ENGINEERING, FINANCE, AND SCIENCE
  • DISTRIBUTED, PARALLEL, AND CLUSTER COMPUTING
  • MATHEMATICAL SOFTWARE
  • NUMERICAL ANALYSIS
  • NUMERICAL ANALYSIS