Cloud DDC Sharing for Faster Unreal Engine Collaboration
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Solution Overview
Problem
Conventional Derived Data Caches (DDC) in Unreal Engine game development are too slow for large projects due to increased data size and development staff, requiring improved techniques for processing.
Innovation Solution
A method and apparatus for modifying engine files using a cloud-based system to receive, distribute, and modify Derived Data Caches (DDCs) across multiple client locations, enabling real-time file system monitoring and high-speed global replication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional Derived Data Cache is used for processing large Unreal Engine projects, then computation time is reduced for average users, but processing speed becomes too slow for large projects with increased data size and development staff
Solution Approach 1:
The patent segments the DDC distribution process by separating the source location (where DDC is generated) from multiple destination locations (where DDC is consumed). The file system watcher at the source location identifies changes and triggers selective distribution of only modified files to multiple destinations, rather than redistributing the entire DDC. This segmentation enables parallel processing across multiple locations simultaneously.
Solution Approach 2:
The patent implements preliminary action by establishing file system watchers at destination locations that monitor for incoming DDC files before actual distribution occurs. The system pre-configures the distribution network and pre-identifies dependent files, so that when changes occur at the source, the distribution can immediately begin without waiting for full DDC generation or manual intervention.
2Ease of operation
If DDC files are distributed to multiple locations for simultaneous development, then collaboration efficiency improves, but file synchronization and version control complexity increases
Solution Approach 1:
The patent implements feedback mechanisms through file system watchers at both source and destination locations. These watchers continuously monitor for file changes and automatically trigger distribution processes. When a file is modified at any location, the watcher detects the change, identifies dependent files, and initiates selective redistribution, creating a closed-loop feedback system that maintains synchronization without manual intervention.
Solution Approach 2:
The distribution system operates autonomously through self-service mechanisms. The file system watchers automatically detect changes, the system identifies dependent files based on pre-established relationships, and the distribution process executes without human intervention. Each location serves itself by monitoring local changes and requesting necessary files from the source or other destinations as needed.
Data Source
AI summary
A method for modifying engine files, the method performed by at least one processor in one or more servers at a cloud based location, the method comprising receiving, by the one or more servers at the cloud based location from at least one host device, a derived data cache (DDC) generated by the at least one host device; distributing the DDC from the one or more servers at the cloud based location to one or more client locations, the one or more client locations performing at least one modification to the DDC; and receiving the modified DDC, by the one or more servers at the cloud based location from the one or more client locations.