Highly-Optimizing and Multi-Target Compiler for Embedded System Models

Abstract

Component and Connector (C&C) models, with their corresponding code generators, are widely used by large automotive manufacturers to develop new software functions for embedded systems interacting with their environment; C&C example applications are engine control, remote parking pilots, and traffic sign assistance. This paper presents a complete toolchain to design and compile C&C models to highly-optimized code running on multiple targets including x86/x64, ARM and WebAssembly. One of our contributions are algebraic and threading optimizations to increase execution speed for computationally expensive tasks. A further contribution is an extensive case study with over 50 experiments. This case study compares the runtime speed of the generated code using different compilers and mathematical libraries. These experiments showed that programs produced by our compiler are at least two times faster than the ones compiled by MATLAB/Simulink for machine learning applications such as image clustering for object detection. Additionally, our compiler toolchain provides a complete model-based testing framework and plug-in points for middleware integration. We make all materials including models and toolchains electronically available for inspection and further research.