Subgraph segmented optimization method based on inter-core storage access, and application

Abstract

Provided are a distributed parallel computing based graph computing method, a distributed parallel computing system and a computer readable medium. A graph computing method comprises: obtaining data of a graph to be computed, the graph comprising a plurality of vertices and edges; storing the graph according to a compressed sparse row format, and storing the graph in a sparse matrix form, wherein all adjacent edges having a same vertex are continuously stored, and an offset array is used to support an index function thereof; and for subgraphs in which the degrees of both source vertices and target vertices are greater than a predetermined threshold, in forward graphs, performing segmentation according to target vertices, i.e., the column of a matrix, and in reverse graphs, performing segmentation according to source vertices, i.e., the row of the matrix, and further dividing the subgraph into a plurality of segmented subgraph (SSG) components, so that a target vertex in each SSG is limited within a preset range. According to the SSG method of the embodiment for a high-degree vertex, the conventional problem that the space-time locality of accessing data of an adjacent vertex is poor due to a large vertex range of a single large graph is avoided or relieved.