Mapping Method of MATLAB/Simulink Model for Embedded Many-Core Platform

Multi-/many-core processors are being increasingly used to reduce power consumption and improve performance. In addition, the use of Model-Based Development for embedded systems has been increasing. Relative to these trends, Model-Based Parallelizer (MBP) has an essential role in parallelizing applications (i.e., Simulink blocks) at the model level. MBP maps Simulink blocks to cores using various types of information such as block characteristics, a C code, and the multi-/many-core hardware implementation. However, MBP does not consider many-core hardware with cluster structures. This paper proposes an algorithm that decides on core allocations by considering cluster structures. The proposed algorithm combines two other algorithms: one algorithm uses the core allocation of MBP and path analysis at the cluster-level and considers the influence of communication contention to decide on cluster allocations, and the other algorithm uses the results of MBP and remaps cluster allocations. The proposed algorithm produces better results than its component algorithms could separately. Evaluations demonstrate that the proposed algorithm obtained the better results than the existing method in terms of execution time on random and real models.