Device-Cloud Rendering Split for Mobile GPU Load Reduction
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Solution Overview
Problem
The computing power gap between lightweight GPUs in mobile devices and PC-level GPUs, particularly in rendering advanced 3D applications like ray tracing, necessitates a more efficient method to achieve high-quality rendering without overburdening the device's GPU.
Innovation Solution
A device-cloud collaborative rendering method where the mobile device performs basic rendering and a cloud server handles advanced rendering preprocessing, fusing the results to deliver high-quality images with reduced computational load on the device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If advanced rendering (ray tracing) is performed on mobile device GPU, then rendering quality is improved, but device power consumption and computational load increase significantly
Solution Approach 1:
The rendering process is divided into two segments: basic rendering performed on the mobile device and advanced rendering preprocessing performed on the cloud server. This segmentation allows the mobile device to handle only essential rendering tasks while offloading computationally intensive advanced rendering to the cloud, thereby improving rendering quality without significantly increasing device power consumption.
Solution Approach 2:
The cloud server acts as an intermediary between the mobile device and the final rendered output. The server receives basic rendering results from the mobile device, performs advanced rendering preprocessing (such as ray tracing), and returns the enhanced results to the mobile device for display. This intermediary approach enables advanced rendering effects without requiring the mobile device to perform all rendering computations locally.
2Manufacturing precision
If advanced rendering preprocessing is performed on cloud server, then device-side rendering quality is improved, but cloud-side computing resource consumption increases
Solution Approach 1:
The cloud server performs only partial advanced rendering preprocessing rather than complete rendering. Specifically, it performs preprocessing tasks such as lighting calculations and shadow maps, while leaving final image composition to the mobile device. This partial action approach provides advanced rendering quality improvements without requiring the cloud server to perform all rendering computations, thereby reducing cloud computing resource consumption.
3Productivity
If mobile device performs only basic rendering, then device load is reduced, but rendering quality gap compared to PC-level GPU persists
Solution Approach 1:
The cloud server performs preliminary advanced rendering preprocessing before the mobile device performs final rendering. This preliminary action includes pre-calculating lighting effects, shadows, and other advanced rendering elements that would be computationally expensive for the mobile device to calculate in real-time. By performing these calculations in advance on the cloud server, the mobile device can achieve higher rendering quality without significantly increasing its real-time computational load.
Data Source
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AI summary
This application discloses a device-cloud collaborative rendering method. The method includes: An electronic device performs basic rendering on a first device-side scene to obtain first basic rendering data; the electronic device sends a scene identifier of the first device-side scene and a first advanced rendering type to a server; the server stores a first cloud-side scene transformed from the first device-side scene for the first advanced rendering type; the electronic device sends first status data to the server; the server updates the first cloud-side scene based on the first status data, and performs preprocessing of the first advanced rendering type on the first cloud-side scene, to obtain first preprocessing data; the server sends the first preprocessing data to the electronic device; and the electronic device obtains a first image based on the first basic rendering data and the first preprocessing data, and displays the first image. In this way, a computing power requirement for and load of a device-side GPU are reduced, so that an electronic device with a low GPU computing power can also present advanced rendering effect, thereby effectively improving user experience.