Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Vector target set balance partition method aiming at topological relation parallel computation

A technology of parallel computing and topological relationship, which is applied in the direction of program startup/switching, multi-program device, etc., can solve problems such as task load balancing that cannot be performed by topological relationship algorithms, and affects computing efficiency, so as to improve parallel computing efficiency and efficient spatial relationship analysis Effect

Inactive Publication Date: 2013-04-17
吴立新 +2
View PDF4 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, the vector target set division method of parallel algorithm mainly has round-robin division method. [1] , Scope division method [1-3] , hash division method [1,4] , mixed division method [1,5] , Space curve division method [6,7] etc., but none of these existing partitioning methods can ensure the task load balance of each process in the topological relational parallel algorithm according to the characteristics of the topological relational algorithm, which affects the computational efficiency

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Vector target set balance partition method aiming at topological relation parallel computation
  • Vector target set balance partition method aiming at topological relation parallel computation
  • Vector target set balance partition method aiming at topological relation parallel computation

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0031] Aiming at the vector object set division method for parallel computing of topological relations, a case is provided below to illustrate the present invention.

[0032] (1) A case of vector target set balanced division method taking into account the number of targets

[0033] The invention uses a balanced division method to distribute data to different processes, calculates whether there is overlap between vector objects (one of topological relations), and outputs the spatial object ID obtained by query. The vector target set in this case is 691,442 parcels (with 4,417,571 points) in a certain area, such as image 3 shown (where image 3 A is the set of parcels used in the case, and image 3 B shows the complexity of the parcel block).

[0034] 1) The vector target set for calculating the spatial topological relationship is DataSet, and the number of objects contained in the vector target set is N=691,442;

[0035] 2) Set the weight W of each vector target i =f(v i...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a vector target set balance partition method aiming at topological relation parallel computation. Vector target topological relation parallel computation belongs to the non-computational intensive algorithm, and in parallel computation, main computation resource consumption is to judge whether minimum bounding rectangles among vector targets are intersected or not, but topological computation only occupies a small part of computation resources. Therefore, vector target partition emphasizes to consider balance of the vector target quantity in each progress rather than to give consideration to geometrical complexity of the vector target. Aiming at vector target topological relation parallel computation, data are assigned to each progress by means of efficient balance partition, so that the vector target quantity among the progresses is balanced, namely, task loads are balanced. By the method, the computation loads among the progresses are highly balanced, and accordingly efficiency of the algorithm is improved, and the efficient vector data partition method is provided for development and service of topological relation software for mass data of single-computer multi-core and single-computer many-core high-performance cluster environments.

Description

technical field [0001] The invention belongs to the field of parallel computing, in particular to a vector target set balanced division method for parallel computing of the vector target topological relationship. Background technique [0002] Topological relationship is a qualitative relationship in which spatial objects remain unchanged under transformations such as extension, movement, and rotation. It plays a very important role in the organization, analysis, and query of spatial data. Topological relationship also plays a very important role in spatial reasoning and spatial query, and is an important content of geographic information systems. With the explosive growth of spatial data volume, the traditional spatial relational serial algorithm can no longer meet the analysis and needs of large-scale spatial data. It is urgent to use the computer parallel architecture to develop a parallel algorithm to meet the large-scale vector target (spatial data) Application requirem...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06F9/48
Inventor 吴立新杨宜舟郭甲腾
Owner 吴立新
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products