Graph rendering method and related equipment thereof

Abstract

The embodiment of the invention provides a graph rendering method. The method comprises the following steps: acquiring vertex data of N vertexes to be rendered; if the load capacity of the GPU is larger than a preset value, M to-be-rendered vertexes are obtained from the N to-be-rendered vertexes according to the vertex data of the N to-be-rendered vertexes, and the M to-be-rendered vertexes are the vertexes visible in the visual angle range of a user; m is a positive integer smaller than N; and transmitting the vertex data of the M vertexes to be rendered to the GPU, so that the GPU performs graphic rendering. According to the method and the device, under the condition that the load capacity of the GPU is relatively large, the invisible vertexes in the visual angle range of the user are removed, so that the number of the vertexes needing to be rendered on the GPU side is reduced, and the load of the GPU is reduced.

Description

technical field [0001] The present application relates to the technical field of image processing, and more particularly, to a graphics rendering method, apparatus, and computer-readable storage medium. Background technique [0002] A graphics processor (graphics processing unit, GPU) is a microprocessor dedicated to image operations, and is often used for graphics rendering. [0003] When performing graphics rendering in traditional solutions, the entire process of image rendering is generally performed by the GPU. However, when the load of the GPU is too large, for example, the amount of operations for graphics rendering is large (such as in the case of heavy graphics display) or the GPU needs to process many other operations (for example, the GPU also participates in graphics rendering while performing graphics rendering). When large-scale scientific computing is used), using the traditional solution for graphics rendering will cause the GPU to be overloaded, which in tu...

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Problems solved by technology

However, when the load of the GPU is too large, for example, the amount of calculation for graphics rendering is relatively large (such as the case of heavy graphics display) or other calculations that the GPU needs to process are relatively large (such as the GPU also participates in graphics rendering while performing graphics rendering). When using large-scale scientific calculations), using the traditional solution for graphics rendering will cause the GPU load to be too high, which will affect the performance of the GPU for image rendering

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