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Super computer big data processing capability testing method based on vertex reordering

A technology of supercomputer and big data processing, which is applied in the fields of electrical digital data processing, computing, and other database retrieval, etc.

Active Publication Date: 2019-04-19
NAT UNIV OF DEFENSE TECH
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  • Abstract
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Problems solved by technology

[0010] The technical problem to be solved by the present invention is: the preprocessing before the BFS traversal is not included in the time-consuming and the high probability of edge relationship between the vertex with high degree and the root node is high, and a supercomputer based on vertex reordering is proposed Big data processing ability test method, reducing the number of memory accesses, avoiding invalid memory accesses to the greatest extent, speeding up the traversal of graphs compared with Graph500, and improving the speed of supercomputer big data processing ability testing

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  • Super computer big data processing capability testing method based on vertex reordering
  • Super computer big data processing capability testing method based on vertex reordering
  • Super computer big data processing capability testing method based on vertex reordering

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Embodiment Construction

[0073] image 3 For the overall flow chart of the present invention, the steps of the present invention are as follows:

[0074] The first step, graph generation. Use the Kronecker graph generator to generate a random graph structure G=(V,E), V is a set of vertices, which contains N V vertices, N V is a positive integer; E is an edge set;

[0075] The second step is to construct an adjacency matrix A that stores the graph G. A ij = 0 means there is no edge between vertex i and vertex j, A ij =1 means there is an edge between vertex i and vertex j, 0≤i≤N V -1, 0≤j≤N V -1, i and j are both positive integers;

[0076] The third step is to preprocess V based on the degree of the vertex. The specific method is as follows:

[0077] 3.1. Traverse each vertex in V and record the degree of each vertex to obtain the set D of vertex degrees.

[0078] The i-th element in D deg(v i ) represents the vertex v i degrees, that is, deg(v i ) vertices and vertex v i There is an edg...

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Abstract

The invention discloses a super computer big data processing capability test method based on vertex reordering, and aims to improve the super computer big data processing capability test speed. technical scheme comprises the following steps of generating an adjoining matrix for a map and a construction map, sorting the vertexes in the graph based on the vertex degrees; carrying out BFS search on the graph by utilizing the sequenced vertex set, wherein the characteristic that the probability of edge association of vertexes with high degrees is also high during the same layer of traversal is utilized, transversing and searching child nodes of nodes in the current layer of vertex set, and transversing and checking the vertexes with high degrees preferentially, so that invalid memory access traversal is reduced to the maximum extent. By adopting the method, the hit rate of the edge relation between the nodes can be improved, invalid memory access times are reduced, unnecessary memory access is avoided to the maximum extent, graph traversal is accelerated, and the testing speed of the big data processing capacity of the super computer is increased.

Description

technical field [0001] The invention relates to a method for testing the large data processing capability of a supercomputer, in particular to a method for testing the large data processing capability of a supercomputer based on vertex reordering. Background technique [0002] Graph structure is one of the most important data structures in big data applications, and has been widely used in many fields, such as social media, bioinformatics, astrophysics, artificial intelligence, data mining, etc. The common feature of these applications is the large amount of data and complex structure, which can often reach billions of edges and trillions of nodes, which leads to higher demands on data storage and computing power. Supercomputers are mainly used for numerical calculations, and most HPC benchmarks use computing power as a measure, such as HPL used by Top 500; in the era of big data where data-intensive applications are widely emerging, Graph500, as an important supplement to T...

Claims

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Application Information

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IPC IPC(8): G06F11/34G06F16/901
CPCG06F11/3409G06F11/3419
Inventor 甘新标曾瑞庚吴涛杨志辉孙泽文刘杰龚春叶李胜国杨博徐涵晏益慧
Owner NAT UNIV OF DEFENSE TECH
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