Decentralized distributed rendering method and system

Abstract

The invention discloses a decentralized distributed rendering method and system. The system comprises multiple client sides (100), a main server (200) and multiple rendering servers (300), wherein each client side (100) is used for presenting a rendering task to the main server (200) and uploading a rendering task material file to the main server (200), the main server (200) is used for dividing each rendering task into multiple sub-tasks, monitoring the working states of the multiple rendering servers (300) and allocating the sub-rendering tasks to a fixed number of idler rendering servers (300) and providing the material file downloading service, and the main server (200) is further used for reading a destination file through a destination file storage path of a database (205) after judging that both the sub-task allocating and rendering work and rendering destination file uploading work are completed and feeding the destination file back to the client sides (100).

Description

technical field [0001] The present invention relates to the technical field of cloud rendering, and more specifically, to a decentralized distributed rendering method and a rendering system. Background technique [0002] The continuous improvement of graphics production personnel's requirements for rendering quality has promoted the development of cloud rendering technology, which has gradually increased the attention of rendering systems based on Client / Server mode, and has begun to be promoted and applied in some fields. However, the rendering system is not perfect and has the following defects: [0003] 1) The main server is under heavy load pressure. In this rendering system, the main server is the only file download center, and all rendering nodes need to download files required for rendering from the main server, such as rendering scenes, textures, textures, materials, and each rendering node is highly dependent on the main server . [0004] 2) The rendering system ...

AI Technical Summary

Problems solved by technology

[0004] 2) The rendering system is prone to network congestion

Since each rendering node needs to download files required for rendering from the main server, when the number of rendering nodes is large and the downloaded files are large, the network pressure on the main server increases, and the network between each rendering node and the main server is prone to congestion. It is very easy to cause the interruption of network connection

[0005] 3) Low utilization of system network resources

During the file rendering process performed by each rendering node after completing the file download work on the main server side, the system network is in an idle state, resulting in low utilization of network resources

[0006] 4) Poor system stability

As the main server is the most important command center, the main server has a heavy workload during the busy period of submitting rendering tasks on the client side, and it is very prone to downtime accidents, causing the entire rendering system to be paralyzed

[0007] 5) Poor system scalability

The increase in the number of rendering nodes will put more pressure on the main server. If the main server performance bottleneck and network bandwidth problems cannot be solved, the scale expansion of rendering nodes will also be limited

Images