Simulation of Modelica Models on the CUDA Architecture

Simulations are very important for many reasons, and finding ways of accelerating simulations are therefore interesting. In this thesis the feasibility of automatically generating simulation code for a limited set of Modelica models that can be executed on NVIDIAs CUDA architecture is studied. The OpenModelica compiler, an open-source Modelica compiler, was for this purpose extended to generate CUDA code. This thesis presents an overview of the CUDA architecture, and looks at the problems that need to be solved to generate efficient simulation code for this architecture. Methods of finding parallelism in models that can be used on the highly parallel CUDA architecture are shown, and methods of efficiently using the available memory spaces on the architecture are also presented. This thesis shows that it is possible to generate CUDA simulation code for the set of Modelica models that were chosen. It also shows that for models with a large amount of parallelism it is possible to get significant speedups compared with simulation on a normal processor, and a speedup of 4.6 was reached for one of the models used in the thesis. Several suggestions on how the CUDA architecture can be used even more efficiently for Modelica simulations are also given