Method for image processing optimization based on breadth first search

Abstract

The invention discloses a method for image processing optimization based on breadth first search (BFS) and belongs to the technical field of computer storage and data processing. The method solves the problem that an existing large-scale image processing system based on an external memory generates plenty of external storage I / O when accessing image data, so that the file cache hit rate is severely affected, and the I / O performance is weakened; and accordingly the efficiency of the image processing system is improved. According to the method, on the premise of no change of an image processing model and user operation complexity, with the goal being fully utilizing external memory device sequence I / O performances and enhancing the system file cache hit rate, the BFS tree data layout scheme aiming at image search type application is provided. Through data layout optimization of image data sets of different sources, types and dimensions, the efficiency of the image processing system is obvious improved.

Description

technical field [0001] The invention belongs to the technical field of computer data processing, and more specifically relates to a graph processing optimization method based on breadth-first traversal. Background technique [0002] Graph is the most commonly used abstract data structure in computer science. Many application scenarios in the real world need to be represented by graph structure, and graph-related processing and applications are almost ubiquitous. Traditional applications such as optimal transportation routes, maps, scientific literature citation relationships, disease outbreak path prediction, etc.; emerging applications such as social network analysis, semantic Web analysis, data mining, protein decomposition, etc. [0003] With the rapid development of graph applications and graph processing technologies, graph algorithm theories emerge in endlessly. Breadth-first search is one of the easiest graph search algorithms and the basis of many important graph al...

AI Technical Summary

Problems solved by technology

However, due to the high relevance and low locality of graph data, and the randomness of graph algorithm access, the traditional storage access mechanism based on spatio-temporal locality optimization in the operating system is difficult to play a role, and graph traversal query is the key to most graph algorithms. How to optimize the I / O of graph query in the external memory mode and speed up the performance of graph traversal becomes the key to efficiently process graph data

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