Topic 11. Parallel Numerical Methods and Applications

The need for high performance computations is driven by the need for large-scale simulations in science and engineering, finance, life sciences etc. This demand goes hand in hand with the necessity to develop highly scalable numerical methods and algorithms that are able to efficiently exploit modern computer architectures. The scalability of these algorithms and methods and their suitability to efficiently utilize the available high performance, but in general heterogeneous, computer resources, is a key point to improve the performance of Computational Science and Engineering applications.

This conference subject aims at providing a forum for presenting and discussing recent developments in parallel numerical algorithms and their implementation on current parallel architectures, including many-core and hybrid architectures. We encourage submissions that address algorithmic design, implementation details, performance analysis, as well as integration of parallel numerical methods in large-scale science and engineering applications.


The focus is on, but not limited to, the following topics:

  • Numerical linear algebra for dense and sparse matrices
  • Iterative solution methods for partial differential equations, including domain decomposition and multigrid
  • Integrators for ODEs and systems of ODEs
  • Solvers for DAEs and systems of DAEs
  • Optimization methods
  • Solution methods for non-linear problems
  • Methods for high-dimensional systems
  • Analysis methods for large data sets
  • Uncertainty quantification
  • Applications of numerical algorithms in science and engineering


Chair: Maya Neytcheva (Uppsala University, Sweden)
Local chair: María Martín (University of A Coruña, Spain)
Yvan Notay (Université Libre de Bruxelles, Belgium)
Peter Arbenz (ETH Zürich, Switzerland)
Enrique S. Quintana (University Jaime I, Spain)
Fred Wubs (University of Groningen, The Netherlands)
Osni Marques (Lawrence Berkeley National Laboratory, USA)