At the age of big data, the information changes quickly. How to extract the key information timely seems to be quite important. Therefore, improving the execution speed of BFS algorithm… Click to show full abstract
At the age of big data, the information changes quickly. How to extract the key information timely seems to be quite important. Therefore, improving the execution speed of BFS algorithm means a lot to the processing of big data. This paper firstly introduces the implementation flow, features and performance evaluation criteria of the breadth-first search algorithm, and secondly introduce the research status of BFS algorithm based on current CPU platform both at home and abroad. Thirdly, this paper optimizes the algorithm by using the local principle of program, load balancing method and so on. Finally, the comparison of the algorithm performance is shown in this paper: the program optimized in this paper gets good performance and could be popularized further in practice.
               
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