uu.seUppsala University Publications
Change search
ReferencesLink to record
Permanent link

Direct link
Data Partitioning Methods and Parallel Block-Oriented PDE Solvers
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis. (Software Aspects of High-Performance Computing)
1998 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Data partitioning methods for block-structured problems within scientific computing have been studied. The applications are variational data assimilation in meteorology, ocean modeling, and airflow simulation with multiblock grids. Parallel computers offer in a cost efficient way the computational power and memory that is needed for these kinds of applications. An appropriate data partitioning is then necessary to get a high parallel efficiency and utilization of the parallel computer.

In the meteorological and oceanographical applications the problem with an irregular workload distribution is treated. In meteorological data assimilation, weather observations are merged together with the dynamical flow model in order to compute an initial state of the atmosphere at a given time. Here, the observations are irregularly distributed in space and time. In ocean modeling the workload varies due to sea depth and ice conditions. New data partitioning methods have been developed for these applications. The new methods are better adapted to the problems and thus give higher efficiency than previous data partitioning methods.

In the multiblock applications an additional difficulty is the irregular data dependencies. The blocks in a multiblock grid are usually of different sizes and irregularly coupled. This makes the data partitioning non-trivial. New methods have been developed and different strategies have been investigated - both experimentally and theoretically - using a compressible Navier-Stokes solver as a model problem. The behavior of the different strategies depends very much on the number of subgrids and their sizes as well as the number of processors.

Moreover, software tools for block-oriented PDE solvers have been constructed. The tools are written in Fortran 90 with an object-oriented design and support explicit finite difference methods and multiblock grids. Programs using the tools run on parallel computers and the proposed data partitioning methods are utilized.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 1998. , 20 p.
Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1104-232X ; 348
Keyword [en]
data assimilation, data partitioning, meteorology, multiblock, Navier-Stokes, object-oriented, oceanography, parallel computing
National Category
Software Engineering
Research subject
Numerical Analysis
URN: urn:nbn:se:uu:diva-149ISBN: 91-554-4158-0OAI: oai:DiVA.org:uu-149DiVA: diva2:161055
Public defence
1998-04-17, Room 2347, Polacksbacken, Uppsala University, Uppsala, 10:15 (English)
Available from: 1998-03-27 Created: 1998-03-27 Last updated: 2015-06-03Bibliographically approved

Open Access in DiVA

No full text
Buy this publication >>

Search in DiVA

By author/editor
Rantakokko, Jarmo
By organisation
Department of Scientific ComputingNumerical Analysis
Software Engineering

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Total: 741 hits
ReferencesLink to record
Permanent link

Direct link