Towards a Benchmark Suite for Modelica Compilers: Large Models

Frenkel, Jens; Schubert, Christian; Kunze, Günter; Fritzson, Peter; Sjölund, Martin; Pop, Adrian

doi:10.3384/ecp11063143

Cited by 15 publications

(10 citation statements)

References 4 publications

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“…This enables a number of optimizations most of which cause expression simplification to be run. It is previously known that the time Modelica backends take to translate a model does not scale linearly to the size of the equations [43], so the findings above should not be surprising.…”

Section: Modelmentioning

confidence: 87%

“…It may then end up with a chain of operations that loops over variable substitutions and expression simplification. The number of operations performed may scale with the total number of variables in the equation system if there is no limitation of the number of iterations that the optimizer may make [43]. This makes some synthetic models hard to debug.…”

Section: Display Of Operationsmentioning

confidence: 99%

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Tools and Methods for Analysis, Debugging, and Performance Improvement of Equation-Based Models

Sjölund¹

2015

Linköping Studies in Science and Technology. Dissertations

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Equation-based object-oriented (EOO) modeling languages such as Modelica provide a convenient, declarative method for describing models of cyber-physical systems. Because of the ease of use of EOO languages, large and complex models can be built with limited effort. However, current state-of-the-art tools do not provide the user with enough information when errors appear or simulation results are wrong. It is of paramount importance that such tools should give the user enough information to correct errors or understand where the problems that lead to wrong simulation results are located. However, understanding the model translation process of an EOO compiler is a daunting task that not only requires knowledge of the numerical algorithms that the tool executes during simulation, but also the complex symbolic transformations being performed.As part of this work, methods have been developed and explored where the EOO tool, an enhanced Modelica compiler, records the transformations during the translation process in order to provide better diagnostics, explanations, and analysis. This information is used to generate better error-messages during translation. It is also used to provide better debugging for a simulation that produces unexpected results or where numerical methods fail.Meeting deadlines is particularly important for real-time applications. It is usually essential to identify possible bottlenecks and either simplify the model or give hints to the compiler that enable it to generate faster code. When profiling and measuring execution times of parts of the model the recorded information can also be used to find out why a particular system model executes slowly.Combined with debugging information, it is possible to find out why this system of equations is slow to solve, which helps understanding what can be done to simplify the model. A tool with a graphical user interface has been developed to make debugging and performance profiling easier. Both debugging and profiling have been combined into a single view so that performance metrics are mapped to equations, which are mapped to debugging information.The algorithmic part of Modelica was extended with meta-modeling constructs (MetaModelica) for language modeling. In this context a quite general approach to debugging and compilation from (extended) Modelica to C code was developed. That makes it possible to use the same executable format for simulation executables as for compiler bootstrapping when the compiler written in MetaModelica compiles itself.Finally, a method and tool prototype suitable for speeding up simulations has been developed. It works by partitioning the model at appropriate places and compiling a simulation executable for a suitable parallel platform. Populärvetenskaplig sammanfattningSom ingenjör lär man sig att förstå världen genom ekvationer. För att beskriva eller modellera ett fysikaliskt system, till exempel vid utveckling av en produkt, vill ingenjören använda sig av de ekvationer som han eller hon lärt sig från böcker eller fö...

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Section: Modelmentioning

confidence: 87%

Section: Display Of Operationsmentioning

confidence: 99%

Tools and Methods for Analysis, Debugging, and Performance Improvement of Equation-Based Models

Sjölund¹

2015

Linköping Studies in Science and Technology. Dissertations

Self Cite

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“…It may then end up with a chain of operations that loops over variable substitutions and expression simplification. Frenkel et al (2011) prove that the number of operations performed may scale with the total number of variables in the equation system if there is no limitation of the number of iterations that the optimizer may take. This makes some synthetic models very hard to debug.…”

Section: Presentation Of Operationsmentioning

confidence: 99%

Integrated Debugging of Modelica Models

Pop

Sjölund

Asghar

et al. 2014

MIC

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The high abstraction level of equation-based object-oriented (EOO) languages such as Modelica has the drawback that programming and modeling errors are often hard to find. In this paper we present integrated static and dynamic debugging methods for Modelica models and a debugger prototype that addresses several of those problems. The goal is an integrated debugging framework that combines classical debugging techniques with special techniques for equation-based languages partly based on graph visualization and interaction.To our knowledge, this is the first Modelica debugger that supports both equation-based transformational and algorithmic code debugging in an integrated fashion.

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“…Studies have been developed testing how compilers work on large scale models recognizing their limitations on that area (Frenkel et al, 2011;Sezginer, 2014Sezginer, -2015Casella, 2015). In (Jens Frenkel, 2012) particularly, the authors study different causalization (matching) algorithms applied to large scale models and conclude that the PF+ algorithm (by Duff) is the best choice as it achieves linear performance on the tested cases.…”

Section: Related Workmentioning

confidence: 99%

Efficient Compilation of Large Scale Dynamical Systems

Bergero

Botta²,

Campostrini³

et al. 2015

Linköping Electronic Conference Proceedings

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In this work, we present a novel methodology to efficiently compile large scale dynamical systems described as Modelica models, and its implementation in a prototype Modelica Compiler called ModelicaCC. The methodology allows to perform the different stages of the compilation process without expanding the content of repetitive structures so the resources (CPU time and memory) used by the compiler result independent on the model size. Besides introducing the methodology with their algorithms and the implementation in the ModelicaCC compiler, we analyze their efficiency comparing its performance with that of OpenModelica in different large scale models.

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Towards a Benchmark Suite for Modelica Compilers: Large Models

Cited by 15 publications

References 4 publications

Tools and Methods for Analysis, Debugging, and Performance Improvement of Equation-Based Models

Tools and Methods for Analysis, Debugging, and Performance Improvement of Equation-Based Models

Integrated Debugging of Modelica Models

Efficient Compilation of Large Scale Dynamical Systems

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