liu.seSearch for publications in DiVA
Change search
ReferencesLink to record
Permanent link

Direct link
Object Oriented Mathematical Modelling and Compilation to Parallel Code
Linköping University, Department of Computer and Information Science. Linköping University, The Institute of Technology.
Linköping University, Department of Computer and Information Science, PELAB - Programming Environment Laboratory. Linköping University, The Institute of Technology.ORCID iD: 0000-0002-3435-4996
1997 (English)In: Parallel Computing in Optimization / [ed] Athanasios Migdalas, Panos M. Pardalos and Sverre Storøy, Kluwer Academic Publishers, 1997Chapter in book (Other academic)
Abstract [en]

The current state of the art in programming for scientific computing is still rather low-level. The mathematical model behind a computing application usually is written using pen and paper, whereas the corresponding numerical software often is developed manually in Fortran or C. This is especially true in application areas such as mechanical analysis, where complex non-linear problems are the norm, and high performance is required. Ideally, a high-level programming environment would provide computer support for these development steps. This motivated the development of the ObjectMath system. Using ObjectMath, complex mathematical models may be structured in an object oriented way, symbolically simplified, and transformed to efficient numerical code in C++ or Fortran.

However, many scientific computing problems are quite computationally demanding, which makes it desirable to use parallel computers. Unfortunately, generating parallel code from arbitrary mathematical models is an intractable problem. Therefore, we have focused most of our efforts on a specific problem domain where the main computation is to solve ordinary differential equation systems where most of the computing time is spent in application specific code, rather than in the serial solver kernel. We have investigated automatic parallelisation of the computation of ordinary differential equation systems at three different levels of granularity: the equation system level, the equation level, and the clustered task level. At the clustered task level we employ domain specific knowledge and existing scheduling and clustering algorithms to partition and distribute the computation.

Place, publisher, year, edition, pages
Kluwer Academic Publishers, 1997.
, Applied optimization, 7
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
URN: urn:nbn:se:liu:diva-110157ISBN: 0-7923-4583-5OAI: diva2:743186
Available from: 2014-09-03 Created: 2014-09-03 Last updated: 2014-10-02

Open Access in DiVA

No full text

Other links

Find book at a Swedish library/Hitta boken i ett svenskt bibliotekFind book in another country/Hitta boken i ett annat land

Search in DiVA

By author/editor
Andersson, NiclasFritzson, Peter
By organisation
Department of Computer and Information ScienceThe Institute of TechnologyPELAB - Programming Environment Laboratory
Electrical Engineering, Electronic Engineering, Information 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: 78 hits
ReferencesLink to record
Permanent link

Direct link