面向异构处理平台任务调度的麻雀优化算法OA

In view of the problems of unbalanced distribution task quantity of the each precessor,incomplete performance of the each processor and inefficient system operation in heterogeneous signal processing platform,a spar-row optimization algorithm for heterogeneous processing platform is proposed in this study,which takes advantage of the strong global optimization ability of sparrow algorithm and efficient working mechanism within sparrow population.Based on the classical sparrow algorithm,this study proposes a binary or codec rule that meets the task scheduling,and maps discrete task assignment scheme to continuous sparrow position information.The processor load balance in-dex is taken as the fitness function and the optimal solution is selected in each iteration.When the sparrow traverses the task,the task priority shunt sorting strategy is adopted to adopt different computing formulas for communication-intensive tasks and computing dense tasks to obtain the order of traversing more in accordance with the characteristics of the task,and generates random tasks.Finally,the proposed algorithm is compared with the ICPA(Improved Criti-cal Path Agorithm).The simulation results show that when compared with the ICPA,the an average optimization rate of load balance index of the proposed algorithm is 60%,and the load of each processor is more balanced,and the o-verall performance of the heterogeneous processing platform can be better utilized.