Efficient Code Generation for Data-Intensive Simulink Models via Redundancy Elimination
Zehong Yu, Zhuo Su, Yu Jiang, Aiguo Cui, Rui Wang · 2024
Simulink has emerged as the fundamental infrastructure that supports modeling, simulation, verification, and code generation for embedded software development. To improve the performance of the code generated from Simulink models, state-of-the-art code generators employ various optimization techniques, such as expression folding, variable reuse, and parallelism. However, they overlook the presence of redundant calculations within data-intensive models widely used to perform substantial data processing in embedded scenarios, which can significantly undermine the efficiency and performance of the generated code.