Parallel Video Encoder Segmentation for Data Dependency Management
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Solution Overview
Problem
The challenge in video encoding on multi-processor platforms with more than two processor cores is the data dependency issue, which slows down the encoding process or reduces the quality of the video stream due to spatial and temporal redundancies between video pixels, making it difficult to optimize parallel video encoding effectively.
Innovation Solution
The solution involves a parallel video encoding method where a master/server encoder unit coordinates client/slave encoder units to encode different sections of a video picture in parallel, using a task package that includes encoding instructions and constraints, and employing techniques like mode search, motion compensation, and entropy coding to manage data dependencies and optimize the encoding process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If parallel encoding of multiple sections is implemented, then encoding speed is improved, but data dependency issues cause quality degradation or process slowdown
Solution Approach 1:
The video picture is divided into multiple sections that can be encoded in parallel by different processor cores. Each section is processed independently to eliminate data dependencies, allowing simultaneous encoding operations while maintaining quality through proper section management and coordination.
2Reliability
If sequential encoding is used to avoid data dependencies, then encoding quality is maintained, but encoding delay becomes very large
Solution Approach 1:
By segmenting the video picture into multiple independent sections, the system enables parallel processing that reduces encoding delay while maintaining quality. Multiple sections can be processed simultaneously without waiting for data dependencies to resolve, thus reducing overall encoding time.
Solution Approach 2:
The system performs preliminary actions by pre-processing and preparing encoding parameters for multiple sections before actual encoding begins. This allows the encoding process to proceed more efficiently with reduced delays, as necessary data and parameters are ready in advance for parallel processing.
3Productivity
If artificial data isolations are created to fill inaccessible data dependencies, then encoding process continues, but encoding quality is reduced
Solution Approach 1:
The video picture is segmented into sections where data dependencies are naturally managed through proper section boundaries. This segmentation allows the encoding process to continue without creating artificial data isolations, as each section processes its data independently with clear dependency management, thus maintaining both continuity and quality.
Data Source
AI summary
Mode searching and early termination of a video picture may include determining the cost value of a simple intra-mode prediction of the video picture; determining the cost value of an inter-mode prediction of the video picture; determining a threshold value based on a given quantization parameter (QP); comparing the cost value of the simple intra-mode prediction to the sum of the cost value of the inter-mode prediction and the threshold value; and performing a mode-prediction of the video picture in accordance with the result obtained. Fast compression of variable length symbols may include receiving a variable length symbol with one or more tokens; combining the one or more tokens in the variable length symbol to form a token combination; and determining a bit representation of the token combination in correspondence to a probability threshold associated with the token combination.