Graphics Pipeline Cache Reconstruction via Differential Privacy
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Solution Overview
Problem
Cloud-based gaming platforms face performance degradation due to pipeline cache misses, which result in frame sputtering and increased load times, and existing solutions require exhaustive cache generation that is difficult to achieve without manually playing through all video game configurations.
Innovation Solution
The system reconstructs graphics pipeline caches for current client gaming sessions using pipeline structures generated during previous sessions, initializing graphics pipelines to reduce rendering times and incorporating anonymization to ensure user privacy by storing only anonymized pipeline structures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If exhaustive pipeline caches are generated to prevent pipeline cache misses, then rendering performance is improved, but the complexity of cache generation increases significantly
Solution Approach 1:
The system performs preliminary actions by collecting pipeline structure data during previous gaming sessions and storing it in a database. This pre-collected data is then used to reconstruct pipeline caches for current sessions, eliminating the need for exhaustive real-time cache generation and reducing both complexity and load times.
Solution Approach 2:
The system creates copies of pipeline structure data from previous sessions and stores them in a database. These copied structures are then reconstructed and used as pipeline caches for current gaming sessions, avoiding the need to generate exhaustive caches from scratch each time.
2Loss of time
If pipeline structure data is collected from previous sessions to reconstruct caches, then load times are reduced, but user privacy concerns increase
Solution Approach 1:
The system extracts and removes personally identifiable information from pipeline structure data collected during gaming sessions. By taking out sensitive user information while retaining the essential pipeline structure data, the system reduces privacy risks while still enabling effective cache reconstruction for performance improvement.
3Manufacturing precision
If manual playthrough of all game configurations is performed to build caches, then cache completeness is improved, but productivity decreases
Solution Approach 1:
The system enables self-service by automatically collecting pipeline structure data during normal gaming sessions without requiring manual intervention. The data is gathered organically as players game, and the system automatically processes and stores this data for future cache reconstruction, eliminating the need for manual playthrough of all configurations.
Data Source
AI summary
A graphics pipeline cache reconstruction operation is implemented to reconstruct one or more graphics pipeline caches for a current client gaming session based on one or more pipeline structures. The pipeline structures each represent a graphical object rendered during a respective previous client gaming session and are used to reconstruct one or more graphics pipeline caches that include graphics pipeline cache objects related to the graphical objects of the pipeline structures. These graphics pipeline cache objects are used to initialize one or more graphics pipelines used to render the graphical objects in a gaming application for a current client gaming session.


