Graph model calculation method and device
A graph model and parallel computing technology, applied in the field of electronic information, can solve the problems of high communication overhead and reduce the computing performance of graph model computing, and achieve the effect of reducing communication overhead and improving computing performance.
Inactive Publication Date: 2015-09-16
HUAWEI TECH CO LTD +1
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[0003] However, the current graph model often contains hundreds of millions of vertices and hundreds of millions of edges. In the fine-grained parallel computing method, a large number of vertices and edges in the graph model require a large number of computing devices to store and calculate, because every two Communication between computing devices is required, and the communication overhead between a large number of computing devices is too large, which reduces the computing performance of graph model computing
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[0063] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.
[0064] The technical solutions provided by the embodiments of the present invention can be applied to a layered system, such as figure 1 As shown, the hierarchical system includes at least two clusters, one cluster includes at least one node, and the node participates in fine-grained parallel computing. Wherein, a node can be a physical computing device such as a computer, or a virtual machine processing calculation in the system, etc., and a cluster can be a ...
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The embodiment of the invention discloses a graph model calculation method and device, and relates to the technical field of electronic information. In the graph model calculation process, the communication overhead among calculation equipment or nodes can be reduced, and the calculation performance of the graph model calculation can be improved. The method comprises the steps that graph model data are received and divided into at least two data sets; a cluster grouping configuration file is acquired, according to the cluster grouping configuration file, the nodes are divided into at least two clusters, and the cluster grouping configuration file is used for configurating a cluster dividing method; the data sets are imported into the clusters, fine-grained parallel calculation is performed according to the nodes in the clusters, and a coarse-grained and fine-grained parallel calculation result is obtained by utilizing the fine-grained parallel calculation result of each cluster. The graph model calculation method and device are suitable for being used in the scene of calculating the graph model data.
Description
technical field [0001] The invention relates to the technical field of electronic information, in particular to a method and device for graph model calculation. Background technique [0002] At this stage, graph models are widely used in various fields, such as: expressing the Internet, social networks, protein interaction networks, etc. as data structures of graph models, and then analyzing and mining graph models to achieve more convenient Internet, social network, protein interaction network and other data are analyzed and mined. However, with the growth of data, the graph model often contains hundreds of millions of points and hundreds of millions of edges. The data scale of the graph model has exceeded the memory capacity of a computer. Therefore, in the existing technology, the Pregel distributed Parallel framework or GraphLab distributed parallel framework to process graph models. These two distributed parallel frameworks support fine-grained parallel computing metho...
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Inventor 王蕾冯子畅冯晓兵
Owner HUAWEI TECH CO LTD