MetaModelica: A Unified Equation-Based Semantical and Mathematical Modeling Language

Pop, Adrian; Fritzson, Peter

doi:10.1007/11860990_14

Cited by 17 publications

(16 citation statements)

References 11 publications

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“…Its long-term development is supported by a nonprofit organization The Open Source Modelica Consortium (OSMC) [10]. The Programming Environments Laboratory (PELAB) at Linköping University, together with OSMC, is developing the OpenModelica Compiler (OMC) for the Modelica language (including the MetaModelica [51], ParModelica [19] and Optimica [4] extensions) and the accompanying simulation environment.…”

Section: Openmodelicamentioning

confidence: 99%

Automatic and Explicit Parallelization Approaches for Mathematical Simulation Models

Gebremedhin¹

2015

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The move from single-core processor systems to multi-core and many-processor systems comes with the requirement of implementing computations in a way that can utilize these multiple computational units efficiently. This task of writing efficient parallel algorithms will not be possible without improving programming languages and compilers to provide the supporting mechanisms. Computer aided mathematical modeling and simulation is one of the most computationally intensive areas of computer science. Even simplified models of physical systems can impose a considerable computational load on the processors at hand. Being able to take advantage of the potential computational power provided by multi-core systems is vital in this area of application. This thesis tries to address how to take advantage of the potential computational power provided by these modern processors in order to improve the performance of simulations, especially for models in the Modelica modeling language compiled and simulated using the OpenModelica compiler and run-time environment.Two approaches of utilizing the computational power provided by modern multi-core architectures for simulation of Mathematical models are presented in this thesis: automatic and explicit parallelization respectively. The automatic approach presents the process of extracting and utilizing potential parallelism from equation systems in an automatic way without any need for extra effort from the modelers/programmers. This thesis explains new and improved methods together with improvements made to the OpenModelica compiler and a new accompanying task systems library for efficient representation, clustering, scheduling, profiling, and executing complex equation/-task systems with heavy dependencies. The explicit parallelization approach allows utilizing parallelism with the help of the modeler or programmer. New programming constructs have been introduced to the Modelica language in order to enable modelers to express parallelized algorithms. The OpenModelica compiler has been improved accordingly to recognize and utilize the information from these new algorithmic constructs and to generate parallel code for enhanced computational performance, portable to a range of parallel architectures through the OpenCL standard. This work has been supported by Vinnova in the RTSIM

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Section: Openmodelicamentioning

confidence: 99%

Automatic and Explicit Parallelization Approaches for Mathematical Simulation Models

Gebremedhin¹

2015

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“…In order to be compatible with both simple and advanced matching algorithms the Pantelides index reduction had to be reimplemented modifying the interfaces and the compilation process. Since there exists only little experience about the runtime efficiency and comparability of MetaModelica [22], in which the OMC is written, an external C implementation of freely available matching algorithms [15] has been embedded as well.…”

Section: Measurements On Examplesmentioning

confidence: 99%

Survey of appropriate matching algorithms for large scale systems of differential algebraic equations

Frenkel

Kunze

Fritzson

2012

Linköping Electronic Conference Proceedings

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This paper presents a survey on matching algorithms which are required to translate Modelica Models. Several implementations of matching algorithms are benchmarked on a set of physical models from mechanical systems in ODE and DAE representation. The major part of algorithms is based on the Augmenting Paths Method and one algorithm is based on the Push-Relabel Method. The algorithms are implemented in the programming language C and MetaModelica. In addition two cheap matching algorithms are used to jump-start the advanced matching process.

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“…Since modeling of programming languages is often known as meta-modeling, we use the name MetaModelica [8] [11][12] [30] for this slightly extended Modelica.…”

Section: Modeling Language Constructsmentioning

confidence: 99%

“…After several years of discussion and a number of language prototypes, e.g., [3][8] [9][23] [30][32] [37], this approach finally became part of the new Modelica 4 effort started during the 67th Modelica design meeting [22].…”

Section: Introductionmentioning

confidence: 99%

Bootstrapping a Modelica Compiler aiming at Modelica 4

Sjölund

Fritzson

Pop

2011

Linköping Electronic Conference Proceedings

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What does it mean to bootstrap a compiler, and why do it? This paper reports on the first bootstrapping (i.e., a compiler can compile itself) of a full-scale EOO (Equation-based Object-Oriented) modeling language such as Modelica. The Modelica language has been modeled/implemented in the OpenModelica compiler (OMC) using an extended version of Modelica called MetaModelica. OMC models the MetaModelica language and is now compiling itself with good performance. Benefits include a more extensible maintainable compiler, also making it easier to add functionality such as debugging support.This work is in line with the recently started Modelica 4 design effort which includes moving implementation of language features from the compiler to a Modelica Core library, allowing compilers to become smaller while increasing correctness and portability.A number of language constructs discussed for Modelica 4 are already supported in some form by the bootstrapped compiler. Future work includes adapting language constructs according to the Modelica 4 design effort and extracting and restructuring parts of the Modelica implementation from the OMC compiler to instead reside in a Modelica Core library, making the compiler smaller and more extensible.

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MetaModelica: A Unified Equation-Based Semantical and Mathematical Modeling Language

Cited by 17 publications

References 11 publications

Automatic and Explicit Parallelization Approaches for Mathematical Simulation Models

Automatic and Explicit Parallelization Approaches for Mathematical Simulation Models

Survey of appropriate matching algorithms for large scale systems of differential algebraic equations

Bootstrapping a Modelica Compiler aiming at Modelica 4

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