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Adaptive ODE Solvers for Timed Data Flow Models in SystemC-AMS | IEEE Conference Publication | IEEE Xplore

Adaptive ODE Solvers for Timed Data Flow Models in SystemC-AMS


Abstract:

The analog/mixed signal extensions to SystemC effectively tackle the needs for heterogeneous system integration using virtual prototyping. However, they introduce the inh...Show More

Abstract:

The analog/mixed signal extensions to SystemC effectively tackle the needs for heterogeneous system integration using virtual prototyping. However, they introduce the inherent trade-off between accuracy and performance due to the discrete timestep. Besides the discrete-time scheduler, analog solvers are used within SystemC-AMS to solve linear ordinary differential equations (ODEs). In this paper, we derive two methodologies to integrate adaptive ODE solvers into SystemC-AMS that estimate the optimal timestep based on error control. The main advantage of the approaches is the avoidance of time-consuming global backtracking. Instead, they fit well into the execution semantics and scheduling approach of SystemC-AMS. A detailed comparison of both integration schemes is given and they are evaluated using a MEMS accelerometer as classical example of a heterogeneous system.
Date of Conference: 25-27 March 2024
Date Added to IEEE Xplore: 10 June 2024
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Conference Location: Valencia, Spain

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