Parallel digital terrain analysis optimization method based on distributed memory

A technology of digital terrain and optimization method, which is applied in various digital computer combinations, electronic digital data processing, structured data retrieval, etc., can solve the problem of cluster environment without considering data splitting, data and task scheduling methods, parallel computing, Lack of split data dependencies, difficulty in giving quantitative data split optimization methods, etc., to achieve the effect of improving efficiency, improving processing efficiency, and ensuring accuracy

Inactive Publication Date: 2015-05-06
NANJING NORMAL UNIVERSITY
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Problems solved by technology

These research methods not only lack the quantitative issues such as the size of the split data and the dependencies between the split data, but also do not consider the data

Method used

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  • Parallel digital terrain analysis optimization method based on distributed memory
  • Parallel digital terrain analysis optimization method based on distributed memory
  • Parallel digital terrain analysis optimization method based on distributed memory

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Embodiment

[0078] Embodiments of the present invention provide an optimal number of divisions for data division of a slope algorithm for digital terrain analysis. Let the DDG of the slope algorithm be 10.41 and the RFG be 10.15. Suppose the size of the data W to be calculated is 1.69GB, the speed of data distribution V is 72MB / s, and the delay δ of the startup process is 0.2 seconds, then the optimal number of data blocks is;

[0079]

[0080] The minimum computation time is approximately:

[0081]

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Abstract

The invention belongs to the technical field of the cross of digital terrain analysis and parallel computation, and relates to a parallel digital terrain analysis optimization method based on a distributed memory. The parallel digital terrain analysis optimization method comprises a model for the data distributed granularity and the results fusion granularity of parallel digital terrain analysis, a computation method of the mode, a data sequence distributing and scheduling strategy on the basis of the distributed memory, an optimization method of a data fractionation block number which considers the starting and closing expenditure of a computation node, and a cluster node configuration parameter selection method based on an optimal data block number. The parallel digital terrain analysis optimization method can be completely applied to a data fractionation and cluster parameter selection occasion of the high-performance computation of the parallel digital terrain analysis of large-scale mass data, such as the terrain factor extraction of a regular grid parallel interpolation, terrain slope and orientation parallel computation, depression filling parallel computation and the like, can be applied to the high-performance computation of geographic information processing and also can be applied to application occasions, such as spatial decision analysis based on the geographic information, data mining and the like, and processing efficiency is improved.

Description

technical field [0001] The invention belongs to the cross technical field of digital terrain analysis and parallel computing, relates to an optimization method based on data-intensive parallel computing data splitting, and provides a parallel digital terrain analysis-oriented cluster optimization method based on distributed memory parallel computing mode The parameter selection method. Background technique [0002] Digital Terrain Analysis (DTA) is a digital information processing technology for terrain attribute calculation and feature extraction based on Digital Elevation Model (DEM). The digital elevation model (DEM) is a solid ground model that expresses the ground elevation in the form of a set of ordered numerical arrays. It is a branch of the digital terrain model (Digital Terrain Model, referred to as DTM), from which various other terrain feature values ​​can be derived. Parallel digital terrain analysis is the use of parallel computing technology to solve the prob...

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Application Information

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IPC IPC(8): G06F17/30G06F15/16
CPCG06F9/4881G06F9/5061G06F16/29
Inventor 窦万峰李岩
Owner NANJING NORMAL UNIVERSITY
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