Research On Blind-optimization-based Hardware/Software Partitioning Technology

The method of hardware software co-design is always used in embedded systemdesign to shorten the development cycle of the system, while reducing system cost,power consumption, and many other requirements. And the emphasis and difficulty ofhardware software co-design is HW/SW partitioning. The existing algorithms forstatic HW/SW partitioning have sensitive parameter settings, high computationalcomplexity or other problems, while there is less study for dynamic HW/SWpartitioning. So, in the paper, the partitioning and scheduling technologies in HW/SWpartitioning are in-depth studied with the main clue of blind optimization, and thefollowing work is completed.The limitation of1DS algorithm in HW/SW partitioning is analyzed and pointedout, and then a description method based on greedy rule is proposed. The introducedmethod and related theorem make clear the precondition of finding optimumsolutions, and ensure the consistency of the theory and algorithm.The AFSA is introduced to HW/SW partitioning and a novel blind optimizationmethod for HW/SW partitioning is proposed. When AFSA is applied to solve discreteproblems, the optimum solution occurrence probability and the convergence speed arelow. So the improved methods based on random step and neighborhood searching areproposed. Experimental results show that the improved AFSA can achieve results insearch ability and convergence speed superior to original algorithm. Thus theimproved AFSA can execute HW/SW partitioning much more efficiently.The blind optimization method based on SFLA is introduced to HW/SWpartitioning for large-scale systems, and the improved methods based on same stateresetting and double-layer adaptive neighborhood searching are adopted to solve theproblems of poor global searching ability and low convergence efficiency.Experimental results show that, within a shorter run time, the optimum solution ofimproved SFLA is equal to or better than that of the original algorithm, and theoptimum solution occurrence probability is equal to or higher than that of the originalalgorithm. Thus the improved SFLA has better global searching ability and higherconvergence efficiency. Aiming at the task scheduling problem of blind-optimization-based HW/SWpartitioning, the METF algorithm oriented to scheduling length and the MDF, MRFalgorithm oriented to communication storage ability are proposed. Finally, theefficiency of the three algorithms is proved through scheduling experiments withrandom DAGs.Aiming at the task prediction problem of blind-optimization-based dynamicHW/SW partitioning, a task prediction algorithm based on ordered periodic base isproposed. The experiments of task scheduling prediction for selected task sequencesshow that the algorithm has the ability of task prediction and can complete predictiontasks for dynamic HW/SW partitioning.