Object-oriented software tools for parallel PDE solvers

1996 ◽  
Vol 1 (3-4) ◽  
pp. 420-429
Author(s):  
Michael Thuné
2010 ◽  
Vol 8 (3) ◽  
pp. 287-295 ◽  
Author(s):  
I. F. Di Paolo ◽  
Thiago Damasceno Cordeiro ◽  
Jose Adolfo da Silva Sena ◽  
Maria da Conceicao Peraira Fonseca ◽  
Walter Barra ◽  
...  

2006 ◽  
Vol 2 (SPS5) ◽  
pp. 319-324
Author(s):  
Ganghua Lin ◽  
Jiangtao Su ◽  
Yuanyong Deng

AbstractFor developing countries it is very important to derive maximum use of data obtained from their own telescopes. This is not only related to maximizing science returns on capital investment, but also to maximizing science output. In this paper we describe how we are utilizing software tools to realize this goal. This paper discusses the design and main features of our software tools, and planned future developments. The primary vehicle for general data interpretation is through various interactive techniques of data visualization. Our software employs an object oriented approach which facilitates data processing for experienced users as well as being easier to learn for novice users. This leads to greatly increased efficiency in every phase of data analysis. For developing countries the kind of software we are developing and the virtual observatory concept holds out the hope of advancing capability and efficiency in scientific research.


Author(s):  
Michael Thuné ◽  
Krister Åhlander ◽  
Malin Ljungberg ◽  
Markus Nordén ◽  
Kurt Otto ◽  
...  
Keyword(s):  

2020 ◽  
Author(s):  
Dilawar Singh ◽  
Steven S. Andrews

AbstractMotivationSmoldyn is a particle-based biochemical simulator that is frequently used for systems biology and biophysics research. Previously, users could only define models using text-based input or a C/C++ applicaton programming interface (API), which were convenient, but limited extensibility.ResultsWe added a Python API to Smoldyn to improve integration with other software tools such as Jupyter notebooks, other Python code libraries, and other simulators. It includes low-level functions that closely mimic the existing C/C++ API and higher-level functions that are more convenient to use. These latter functions follow modern object-oriented Python conventions.AvailabilitySmoldyn is open source and free, available athttp://www.smoldyn.org, and can be installed with the Python package managerpip. It runs on Mac, Windows, and [email protected] informationDocumentation is available athttp://www.smoldyn.organdhttps://smoldyn.readthedocs.io.


1992 ◽  
Vol 8 (3) ◽  
pp. 227-238 ◽  
Author(s):  
Dong-Guk Shin ◽  
Changhwan Lee ◽  
Jinghui Zhang ◽  
Kenneth E. Rudd ◽  
Claire M. Berg

Author(s):  
Michael Thuné ◽  
Eva Mossberg ◽  
Peter Olsson ◽  
Jarmo Rantakokko ◽  
Krister Åhlander ◽  
...  
Keyword(s):  

Author(s):  
MANUEL A. PEREIRA REMELHE ◽  
SEBASTIAN ENGELL

Technical systems that include complex physical dynamics as well as extensive discrete event control, require powerful modeling and simulation techniques. As the most adequate means for modeling hybrid physical systems, we advocate the use of object-oriented modeling languages such as Modelica. However, the discrete event models often require the use of dedicated graphical editors that cannot be defined appropriately using Modelica. The purpose of the DES/M modeling environment [10] is to provide such editors for different discrete event formalisms and to translate discrete event models automatically into Modelica components such that a discrete event controller can be integrated easily into Modelica models and simulated using standard Modelica software tools. This contribution presents the main concepts used for the representation of several discrete event formalisms in the Modelica language and discusses the class of discrete event formalisms that can be supported by the DES/M environment.


2006 ◽  
Vol 14 (2) ◽  
pp. 111-139 ◽  
Author(s):  
Andrea Lani ◽  
Tiago Quintino ◽  
Dries Kimpe ◽  
Herman Deconinck ◽  
Stefan Vandewalle ◽  
...  

Object-oriented platforms developed for the numerical solution of PDEs must combine flexibility and reusability, in order to ease the integration of new functionalities and algorithms. While designing similar frameworks, a built-in support for high performance should be provided and enforced transparently, especially in parallel simulations. The paper presents solutions developed to effectively tackle these and other more specific problems (data handling and storage, implementation of physical models and numerical methods) that have arisen in the development of COOLFluiD, an environment for PDE solvers. Particular attention is devoted to describe a data storage facility, highly suitable for both serial and parallel computing, and to discuss the application of two design patterns, Perspective and Method-Command-Strategy, that support extensibility and run-time flexibility in the implementation of physical models and generic numerical algorithms respectively.


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