Research on the construction and simulation of PO-Dijkstra algorithm model in parallel network of multicore platform

Abstract

AbstractThe development of multicore hardware has provided many new development opportunities for many application software algorithms. Especially, the algorithm with large calculation volume has gained a lot of room for improvement. Through the research and analysis, this paper has presented a parallel PO-Dijkstra algorithm for multicore platform which has split and parallelized the classical Dijkstra algorithm by the multi-threaded programming tool OpenMP. Experiments have shown that the speed of PO-Dijkstra algorithm has been significantly improved. According to the number of nodes, the completion time can be increased by 20–40%. Based on the improved heterogeneous dual-core simulator, the Dijkstra algorithm in Mi Bench is divided into tasks. For the G.72 encoding process, the number of running cycles using “by function” is 34% less than using “divided by data,” while the power consumption is only 83% of the latter in the same situation. Using “divide by data” will reduce the cost and management difficulty of real-time temperature. Using “divide by function” is a good choice for streaming media data. For the Dijkstra algorithm, the data is data without correlation, so using a simpler partitioning method according to the data partitioning can achieve good results. Through the simulation results and the analysis of the results of real-time power consumption, we conclude that for data such as strong data correlation of streaming media types, using “divide by function” will have better performance results; for data types where data correlation is not very strong, the effect of using “divide by data” is even better.