Automatic parallelization of simulink applications
The parallelization of Simulink applications is currently a responsibility of the system designer and the superscalar execution of the processors. State-of-the-art Simulink compilers excel at producing reliable and production-quality embedded code, but fail to exploit the natural concurrency available in the programs and to effectively use modern multi-core architectures. The reason may be that many Simulink applications are replete with loop-carried dependencies that inhibit most parallel computing techniques and compiler transformations. In this paper, we introduce the concept of strands that allow the data dependencies to be broken while preserving the original semantics of the Simulink program. Our fully automatic compiler transformations create a concurrent representation of the program, and thread-level parallelism for multi-core systems is planned and orchestrated. To improve single processor performance, we also exploit fine grain (equation-level) parallelism by level-order scheduling inside each thread. Our strand transformation has been implemented as an automatic transformation in a proprietary compiler and with a realistic aeronautic model executed in two processors leads to an up to 1.98 times speedup over uniprocessor execution, while the existing manual parallelization method achieves a 1.75 times speedup.