IO (Input Output) double-buffer interactive multicore processing method for remote sensing image

Abstract

The invention discloses an IO (Input Output) double-buffer interactive multicore processing method for a remote sensing image. The method comprises the following steps of determining the quantity of multicore computing threads according to the quantity of CPU (Central Processing Unit) cores of a processing system; determining various data segmentation strategies according to various remote sensing image processing algorithms; starting each remote sensing image processing computing thread, starting to execute the remote sensing image processing algorithms and sending a data access request and an output request during the period; reading or writing in a data request according to the computing threads, starting a reading-writing data thread, reading image data into buffer memories R1 and R2 in order according to a predetermined reading segmentation strategy, and writing processed result data into writing buffers W2 and W1 in order; and destructing the reading-writing double-buffer and ending the reading-writing thread and each computing thread till the completion of the computing process according to the processing algorithms and the stopping of data reading-writing visit. With the adoption of the IO double-buffer interactive multicore processing method for the remote sensing image, the resource utilization rate of a multicore CPU and the efficiency of disk IO visit are improved, and a contradiction between limited memory space and mass remote sensing data processing is solved.

Description

technical field [0001] The invention relates to a multi-core computing method, in particular to an IO double-buffer interactive multi-core processing method for remote sensing images, belonging to the technical field of computer remote sensing image processing, and used for high-resolution panchromatic, multi-spectral, hyperspectral and radar in remote sensing applications Rapid processing of various types of massive remote sensing images. Background technique [0002] The processing of massive remote sensing images often consumes a lot of time for users. Although computer hardware equipment has been greatly developed, the processing speed of massive remote sensing images is limited. The possible reason is that the underlying data-driven design of the remote sensing image processing algorithm does not fully utilize the CPU computing resources and disk IO resources of the computer, and there are too many calculations or waiting for IO access; or it is due to the data processi...

AI Technical Summary

Problems solved by technology

However, the bottleneck of the calculation speed of most engineered remote sensing image processing algorithms is still the low IO of disk data and the limited memory size, not just on the CPU optimized for multi-core computing.

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