Optimal Implementation of Simulink Models on Multicore Architectures with Partitioned Fixed Priority Scheduling

Model-based design using the Simulink modeling formalism and associated toolchain has gained popularity in the development of real-time embedded systems. However, the current research on software synthesis for Simulink models has a critical gap for providing a deterministic, semantics-preserving implementation on multicore architectures with partitioned fixed-priority scheduling. In this paper, we consider a semantics-preservation mechanism that combines (1) the RT blocks from Simulink, and (2) task offset assignment to separate the time windows to access shared buffers by communicating tasks. We study the software synthesis problem that optimizes control performance by judiciously assigning task offsets, task priorities, and task communication mechanisms. We develop a problem-specific exact algorithm that uses an abstraction layer to hide the complexity of timing analysis. Experimental results show that it may run a few orders of magnitude faster than a direct formulation in integer linear programming.