Processor Inactivity Prediction for Hitch-Free Frame Rendering
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Solution Overview
Problem
Computing devices experience hitches due to the inability to process and commit data for rendering frames before commit deadlines, especially with increasing refresh rates and varying processing requirements, leading to frequent display issues.
Innovation Solution
Predicting periods of processor inactivity and scheduling additional operations during these times to ensure completion before commit deadlines, utilizing prediction engines and power management to optimize processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If the refresh rate is increased, then the display performance is improved, but the time between commit deadlines is reduced leading to more frequent hitches
Solution Approach 1:
The system performs preliminary actions by predicting future operations and executing them during current processor idle periods. The prediction engine identifies operations that will be needed for future frames and schedules them to complete before their respective commit deadlines, preventing hitches while maintaining high refresh rates.
Solution Approach 2:
The system eliminates processor idle time by continuously scheduling useful operations. Instead of leaving the processor inactive during periods between frame commitments, the system fills these gaps with predicted operations that will be needed in the future, ensuring continuous productive work without compromising display timing.
2Productivity
If more data is processed before commit deadlines, then the display performance is improved, but the processor workload increases leading to power consumption issues
Solution Approach 1:
The system dynamically adjusts processor power settings based on the scheduled workload. The power management component monitors the predicted operations and commit deadlines, then optimizes processor frequency and voltage to match the actual computational requirements, avoiding unnecessary power consumption while maintaining productivity.
Solution Approach 2:
The system changes processor operating parameters (frequency, voltage, power state) based on the scheduled workload and time constraints. By analyzing the predicted operations and their deadlines, the system adjusts processor parameters to achieve the required throughput with minimal energy expenditure.
3Reliability
If operations are scheduled to complete before commit deadlines, then hitches are reduced, but the scheduling complexity increases
Solution Approach 1:
The system introduces a prediction engine as an intermediary component that simplifies the scheduling task. Instead of directly managing complex real-time scheduling, the prediction engine forecasts future operations and their timing requirements, allowing the scheduler to work with pre-analyzed data and reduce the complexity of real-time decision-making.
Data Source
AI summary
A computing device performs a first operation before a first commit deadline, resulting in a first frame being rendered and displayed in a first cycle. A second operation is performed, before a second commit deadline, resulting in a second frame being rendered and displayed in a second cycle. A time remaining to a third commit deadline is determined, using the current time. A third operation is predicted, performable before a third commit deadline. An additional operation is predicted, performable for a future cycle. A total processing time for the third and additional operations is determined, being less than the remaining time. The third and additional operations are performed for use in a future cycle. The result of the third operation is used to render a third frame for the third cycle. The result of the additional operation is used to render an additional frame before a future render deadline.