Compute unified device architecture (CUDA) based grid digital elevation model (DEM) neighborhood analysis system and method

Abstract

The invention discloses a compute unified device architecture (CUDA) based grid digital elevation model (DEM) neighborhood analysis system, which comprises a digital input / output (IO) module, a function scheduling module, a kernel function module and a neighborhood analysis operator, wherein the data IO module provides data read-write support; the function scheduling module coordinates execution of a data IO thread and a CUDA kernel function; a plurality of threads are simultaneously started, one thread is used for data IO, the other threads are called worker threads, and the number of the worker threads is equal to the quantity of graphics processing units (GPU) of a host; the kernel function module is used for copying data from an internal memory buffer to a memory of a GPU chip, calling the CUDA kernel function to compute the data, and copying the data from the memory of the GPU chip into an internal memory after computation is finished; and the neighborhood analysis operator is called by the kernel function module and used for executing data computation of a single neighborhood template in neighborhood analysis. By parallel data IO and computation and parallel CUDA, the processing speed of a grid DEM neighborhood analysis process can be greatly improved.

Description

technical field [0001] The invention belongs to the field of high-performance geographic information computing. It specifically relates to a general acceleration system for grid DEM (Digital Elevation Model, digital elevation model) neighborhood analysis based on CUDA (Compute Unified Device Architecture, computer unified architecture system) technology. Background technique [0002] In the field of geographic information system (Geographical Information System, GIS), digital elevation model (Digital Elevation Model, DEM) is often used to describe the spatial distribution of regional landforms. Currently widely used DEM models are divided into two categories: grid DEM and triangular mesh DEM. A grid DEM is an elevation value model of regular grid points within a given range. Neighborhood analysis based on grid DEM (such as slope, aspect analysis, edge detection, filter change, etc.) has become an important type of spatial analysis because it can extract a lot of basic data...

AI Technical Summary

Problems solved by technology

Therefore, this type of analysis faces two problems: one is computationally intensive, and a neighborhood template is required for the calculation of each result value; the other is the large amount of data, and the DEM data of industrial production often reaches the GB level

But CUDA technology also has flaws: its computing model is not general enough

However, these studies only apply an operator to CUDA optimization, and no research has given a more general solution

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