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Fine-grained multithreaded models can provide more opportunities for system performance improvements, but they face large amount of communication overhead. To reduce the communication overhead to improve performance, message aggregation and communication pipeline have been proposed and their advantages have been discussed in previous works. However, when exploiting them in reallife applications, it is challenging to maximize their advantages due to their unrevealed problems. This paper investigates the two communication optimization techniques from the view of their problems to fulfill the studies. We have found that when applying the techniques, message aggregation may have the deadlock problem and latency problem, and communication pipeline may face the ineffective problem and prolog and epilog problem. Based on the basic requirement of allocating the two techniques on an initial schedule, we then present general solutions to avoid or handle the problems. To obtain a minimum schedule length for an initial schedule, we further develop a binary particle swarm optimization-based finegrained communication optimization method to allocate message aggregation and communication pipeline for best performance. The method is also integrated into light and efficient simulink compiler for embedded application multithreaded code generator to generate high quality codes. Experimental results on both synthetic and real-life applications demonstrate the efficiency of the proposed method.

BFCO: A BPSO-Based Fine-Grained Communication Optimization Method for MPSoC