Pipelined Entropy Decoding with Parallel Search Tree Lookup Tables
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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
1Loss of substance
If CABAC (Context Adaptive Binary Arithmetic Coding) 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 distinct hardware modules: context modeling units, binary arithmetic decoding units, and probability update units. Each module handles specific tasks independently, allowing parallel processing while maintaining the complex CABAC algorithm's compression efficiency.
Solution Approach 2:
The patent replaces software-based arithmetic decoding with dedicated hardware circuits that perform binary arithmetic decoding operations. This substitution of mechanical/computational processes with specialized hardware reduces the computational burden while preserving compression performance.
2Device complexity
If serial processing is used in entropy decoding, then implementation simplicity is maintained, but decoding speed deteriorates
Solution Approach 1:
The decoding process is divided into independent stages that can operate in parallel: context modeling, probability calculation, and bitstream processing. Each stage processes different data simultaneously, transforming the serial bottleneck into a parallel architecture that maintains implementation clarity while boosting speed.
Solution Approach 2:
The patent transitions from single-threaded serial processing to multi-threaded parallel processing by introducing multiple decoding units that operate simultaneously on different portions of the bitstream or different symbol sequences, effectively adding a temporal dimension to the processing architecture.
3Speed
If hardware-based parallel processing is implemented, then decoding speed is improved, but device complexity increases
Solution Approach 1:
The patent designs universal decoding units that can handle multiple coding contexts and probability models through configuration rather than dedicated hardware for each case. These multi-functional units reduce overall hardware complexity while maintaining parallel processing capabilities across different decoding scenarios.
Solution Approach 2:
The patent implements a hierarchical hardware architecture where simple lookup tables and probability models are nested within larger decoding units, which are themselves nested within the overall parallel processing framework. This nested structure allows complex functionality to be built from simpler modular components, managing hardware complexity systematically.
Data Source
AI summary
An entropy decoder and method for decoding code words with an indication of associated probability for each code word. The decoder can be operable to receive code words and the indication of associated probability. A branch node block can be in communication with a leaf node block. 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.