Entropy Decoder Lookup Pipeline for Faster CABAC Decoding
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Solution Overview
Problem
Existing entropy decoding processes are bottlenecked by their serial nature, particularly in real-time compression applications, due to the computational demands of entropy encoding/decoding components.
Innovation Solution
A hardware-based entropy decoding engine utilizing N search tree lookup tables processes code words and probability information in a pipelined architecture, where branch and leaf node blocks operate simultaneously across clock cycles to decode code words into phrase words, improving efficiency by parallel processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If CABAC is used for entropy coding, then compression efficiency is improved, but computational complexity increases
Solution Approach 1:
The patent segments the entropy decoding process into multiple parallel decoding engines, each handling a portion of the code stream. This segmentation allows CABAC's complex arithmetic operations to be distributed across multiple units, maintaining high compression efficiency while reducing the computational burden on any single processing unit.
Solution Approach 2:
The patent transitions from sequential processing to parallel processing by introducing multiple decoding engines operating simultaneously. This dimensional change from time-sequential to space-parallel architecture enables the system to maintain CABAC's computational intensity while achieving real-time performance through concurrent operations.
2Device complexity
If serial processing is used for entropy decoding, then implementation simplicity is maintained, but processing speed deteriorates
Solution Approach 1:
The patent divides the code stream into multiple segments that can be processed in parallel by separate decoding engines. Each engine maintains a simplified serial processing architecture, but the overall system achieves high processing speed through the concurrent processing of multiple segments.
Solution Approach 2:
The patent performs preliminary actions by pre-organizing the code stream into parallelizable segments and pre-configuring multiple decoding engines. This preparation enables the system to transition from simple serial processing to accelerated parallel processing without increasing the complexity of individual processing units.
3Speed
If parallel processing is implemented for entropy decoding, then processing speed is improved, but implementation complexity increases
Solution Approach 1:
The patent segments both the code stream and the processing architecture into identical, reusable units. This uniform segmentation allows parallel processing to be implemented by simply replicating the same decoding engine multiple times, reducing implementation complexity compared to designing complex inter-connected processing units.
Solution Approach 2:
The patent creates a universal decoding engine that can process any segment of the code stream. This multi-functional unit can be replicated and configured in parallel, achieving high processing speed while keeping individual unit complexity low. The same engine design serves multiple purposes across different parallel channels.
Data Source
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AI summary
An entropy decoder and method for decoding code words with an indication of associated probability for each code word. The decoder may include an input buffer in communication with a branch node block, the branch node block in communication with a leaf node block. The input buffer operable to receive code words and the indication of associated probability. The branch node block comprising one or more branch node lookup tables and branch node control logic. The branch node control logic operable to process a code word in the input buffer using a selected table from the one or more branch node lookup tables to obtain leaf node information and a bit count of a code word size, the branch control logic further operable to refresh the input buffer to replace the bit count of the code word size and to make the leaf node information and the table selection available to the leaf node block. The leaf node block may include one or more leaf node lookup tables and leaf node control logic. The leaf node control logic operable to process the leaf node information and the table selection made available by the branch node block to obtain leaf node contents.