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Parallel Radius-Stepping method and system for calculating single-source shortest path on large-scale graph

A single-source shortest path, shortest path technology, applied in the field of graph computing, can solve problems such as low efficiency, and achieve the effect of improving efficiency, improving running speed, and fast computing speed

Pending Publication Date: 2022-07-12
SUN YAT SEN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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This scheme also has the problem of inefficiency

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  • Parallel Radius-Stepping method and system for calculating single-source shortest path on large-scale graph
  • Parallel Radius-Stepping method and system for calculating single-source shortest path on large-scale graph
  • Parallel Radius-Stepping method and system for calculating single-source shortest path on large-scale graph

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Embodiment 1

[0051] This embodiment provides a parallel Radius-Stepping method for calculating single-source shortest paths on large-scale graphs, such as figure 1 shown, including the following steps:

[0052] S1: For the large-scale graph to be calculated, maintain a temporary shortest path and a set S for all vertices in the large-scale graph, and the set S is a subset of the points in the large-scale graph;

[0053] S2: Divide all the vertices in the large-scale graph into several parts and assign them to different sub-processes;

[0054] S3: Calculate an upper bound according to the temporary shortest path of each vertex, the set S and the Radius function, and filter the vertices that need to be processed according to the upper bound;

[0055] S4: The corresponding vertices are processed by each sub-process to obtain the updated temporary shortest path;

[0056] S5: The root process summarizes the updated temporary shortest path obtained after processing by all sub-processes, and th...

Embodiment 2

[0073] On the basis of Embodiment 1, this embodiment discloses the specific implementation content:

[0074] The platform used in the embodiment is an AMD R5-3500U CPU (8GB) computer, the operating system used is the Linux subsystem in Windows 10, and the number of CPUs is 4. The programming language to implement the algorithm is Python, and version 3.6.9 uses the Python library mpi4py built on MPI to implement the parallel algorithm.

[0075] The pseudo code of the algorithm of this embodiment is shown in Table 1:

[0076] figure 2 , 3 , 4 and 5 are 4 common network graphs: BA scale-free network, ER random network, regular network and WS small world network. According to the number of vertices and the number of edges, a total of 6 kinds of graphs are generated. The value of the weight ranges from 1 to 100. According to the ratio of the number of vertices and the number of edges, the graphs of these six specifications can be divided into sparse graphs and dense graphs. Ea...

Embodiment 3

[0088] Based on Embodiment 1, this embodiment provides a parallel Radius-Stepping system for calculating single-source shortest paths on large-scale graphs, such as Image 6 shown, including:

[0089] A maintenance module, for the large-scale graph to be calculated, the maintenance module maintains a temporary shortest path and a set S for all vertices in the large-scale graph, and the set S is a subset of the points in the large-scale graph;

[0090] a division and allocation module, which divides all the vertices in the large-scale graph into several parts and allocates them to different sub-processes respectively;

[0091] an upper bound calculation module, the upper bound calculation module calculates an upper bound according to the temporary shortest path, the set S and the Radius function of each vertex, and according to the upper bound, filters the vertices that need to be processed;

[0092] a sub-process processing module, wherein the sub-process processing module ut...

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Abstract

The invention discloses a parallel Radius-Stepping method and system for calculating a single-source shortest path on a large-scale graph, and the method comprises the following steps: dividing vertexes in graph data into a plurality of parts in advance in an algorithm, carrying out the processing of a corresponding process, determining a vertex set needing to be processed, and carrying out the calculation of a single-source shortest path on the large-scale graph, and each process respectively processes the vertex of the corresponding part, and then summarizes the information. Compared with a serial Radius-Stepping algorithm, the method has the advantages that the updating of the temporary shortest path is processed in parallel by utilizing a plurality of processes, so that the calculation speed is higher, the efficiency in practical application is further improved, and the running speed of the Radius-Stepping algorithm under the condition that the graph data scale is too large is improved.

Description

technical field [0001] The invention relates to the field of graph computing, and more particularly, to a parallel Radius-Stepping method and system for computing single-source shortest paths on large-scale graphs. Background technique [0002] The Radius-Stepping algorithm is a serial algorithm. Through the algorithm, a predefined function is passed. The input of the function is a certain vertex and the output is a positive real number, so that the inner loop step size is a continuously revised value. In addition, the Radius-Stepping algorithm is faster on the (k, ρ) graph, and the efficiency of the algorithm can be improved if the graph is converted to a (k, ρ) graph in advance. [0003] However, when the Radius-Stepping algorithm processes the single-source shortest path on a large-scale graph, it cannot calculate the single-source shortest path in real time, and the calculation efficiency is relatively slow. [0004] The prior art discloses a large-scale graph data proc...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F9/50
CPCG06F9/5066G06F2209/5017Y02D10/00
Inventor 姚正安王业智王锦祥施章灿
Owner SUN YAT SEN UNIV