Shuffled frog-leaping based division method of software and hardware

Abstract

The invention provides a shuffled frog-leaping based division method of software and hardware. The method comprises the steps of determining the maximum iterations of the algorithm at the initial; calculating the area and time cost of the hardware in the corresponding software and hardware division scheme corresponding to each frog; descending and sequencing the whole frog group according to the adaptive fitness of individual fog; updating the fog groups in each group at a plurality of times to enable the adaptive fitness of the worst frog in the group to be prior to that of the previous frog as well as meeting the system limitation condition; updating the optimal frog in the group by the random updating method in case of failing to update; shuffling the whole frog groups; finding the global optimal solution as the optimal software and hardware division scheme after the iteration is done. According to the method, the sub-task of one embedded composite system is divided through a processor, and meanwhile, the searching and the optimizing capacity of the system are improved; the optimal software and hardware division scheme can be found, and as a result, the task performing efficiency of the system can be increased.

Description

technical field [0001] The invention relates to a software and hardware division technology in system software and hardware collaborative design. In particular, it relates to a software and hardware division method based on shuffle leapfrog for implementing complex tasks in an embedded system. Background technique [0002] 1. Introduction to Shuffle Leapfrog Algorithm [0003] Shuffled Frog Leap Algorithm (SFLA) is a new swarm intelligence optimization algorithm, whose idea comes from the migration and foraging behavior of frog groups. The bionic behavior of the shuffled leapfrog algorithm can be described as: a group of frogs live in a depression, and each frog has its own thoughts. In order to find food, each frog will jump to the frog that is closer to the food to shorten the distance between itself and the food. At the same time, every time the frog group completes an update, the individual frogs will exchange and share information to improve the search for food of the...

AI Technical Summary

Problems solved by technology

[0014] However, the existing algorithms have problems such as poor global search ability and slow convergence speed.

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