Scalable Memory Access for Video Encoding
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Solution Overview
Problem
Conventional video data compression methods are computationally intense and require significant memory bandwidth, which can be inefficient and resource-intensive.
Innovation Solution
A system and method for improved encoding of compressed video data that employs a real-time scheduling system to differentiate between required and optional requests for video data, prioritizing required requests and dynamically determining the subset of reference data needed for motion estimation and compensation, while maximizing video coding quality and optimizing memory access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If video data is compressed to reduce bandwidth and memory usage, then memory bandwidth consumption is reduced, but computational intensity increases
Solution Approach 1:
The patent segments video data into reference data and non-reference data, and further segments reference data into required and optional portions. By dividing the data access pattern into hierarchical levels (reference vs. non-reference, required vs. optional), the system can selectively compress and prioritize different segments, reducing overall memory bandwidth while managing computational load through targeted processing of only essential data segments.
2Reliability
If all requested video data is serviced to maintain video quality, then video coding quality is maintained, but memory bandwidth consumption increases
Solution Approach 1:
The patent applies local quality by differentiating service levels for different data segments. Required reference data receives high-priority servicing to maintain essential video quality, while optional reference data and non-reference data receive lower-priority or deferred servicing. This localized quality approach ensures critical video reconstruction functions are maintained while reducing overall memory bandwidth consumption by selectively servicing only essential data portions.
3Reliability
If computational resources are increased to improve video encoding, then video coding quality improves, but device complexity increases
Solution Approach 1:
The patent implements dynamic resource allocation through a real-time scheduling system that adapts to current system conditions. The scheduling system dynamically prioritizes memory access requests based on data type (reference vs. non-reference) and urgency (required vs. optional), allowing the system to optimize video coding quality according to available computational resources without requiring fixed high-complexity hardware. This dynamic approach enables quality adaptation without proportional increases in device complexity.
Data Source
AI summary
Presented herein are system(s), method(s), and apparatus for scalable memory access. One example, among others, is a system for requesting services. The system includes one or more requesting node(s) for performing a function with real-time requirements, such as making requests. The one or more requesting node(s) indicates whether each of said requests is required or optional.