Mapping Method Usable with Clustered Many-core Platforms for Simulink Model

抄録

Multi/many-core processors are being increasingly used to reduce power consumption and improve performance. The use of model-based development for embedded systems has also been increasing. Relative to these trends, the model-based parallelizer or MBP has an essential role in parallelizing applications at the model level. MBP maps Simulink blocks to cores using various types of information such as block characteristics, C code, and multi/many-core hardware implementation. However, MBP does not consider many-core hardware with cluster structures such as Kalray MPPA2-256 processor which contains 16 clusters of 16 cores for 256 general-purpose cores in total. This paper proposes an algorithm that determines 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 effects from communication contention when determining cluster allocations, and the other algorithm uses the results from MBP and remaps cluster allocations. The proposed algorithm produces better results than its component algorithms could produce separately. Evaluations demonstrate that the proposed algorithm obtained the best results among four methods in terms of execution time on Simulink models.