Huffman Tree Reuse for Faster Dynamic Block Decompression
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Solution Overview
Problem
The inefficiency in decompression processes due to the repeated use of Huffman trees in data compression, which leads to slower decompression speeds and reduced computing efficiency, particularly when dynamic Huffman trees are used, as each data block requires tree reconstruction and preparation.
Innovation Solution
Comparing the encoded Huffman tree to recently used tree compactions to identify matches, allowing the reuse of previous trees for decompression instead of reconstructing new trees from headers, thereby reducing overhead and enhancing decompression speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If dynamic Huffman trees are used for each data block, then compression adaptability is improved, but decompression speed deteriorates due to repeated tree reconstruction
Solution Approach 1:
The patent pre-calculates and stores the compacted representation of the Huffman tree during the compression phase. This preliminary action allows the decompression phase to skip the time-consuming tree reconstruction step by directly using the pre-computed compacted tree data, thereby resolving the speed penalty associated with dynamic Huffman trees.
Solution Approach 2:
The patent creates a compacted copy of the Huffman tree structure that can be rapidly transmitted and reconstructed without performing the full tree-building algorithm during decompression. This copying approach preserves the adaptability benefits while eliminating the computational overhead of repeated tree construction.
2Reliability
If Huffman tree reconstruction is performed for each data block, then decompression accuracy is maintained, but processing time increases
Solution Approach 1:
The patent extracts the essential structural information of the Huffman tree into a compacted representation that can be stored and reused. By separating the critical tree structure from the full reconstruction process, the system maintains decompression accuracy while eliminating redundant computational steps that consume processing time.
Solution Approach 2:
The patent transforms the Huffman tree into a compacted parameter representation that preserves all necessary information for accurate decompression but in a form that requires minimal processing. This parameter transformation maintains reliability while dramatically reducing the time required for each decompression operation.
3Reliability
If full Huffman tree preparation is done before decompression, then decompression correctness is ensured, but computational overhead increases
Solution Approach 1:
The patent performs the computationally intensive tree preparation work during the compression phase and stores the results in a compacted form. This preliminary action shifts the computational burden to the compression stage, allowing the decompression stage to operate with minimal energy consumption while ensuring correctness through the use of the pre-prepared compacted tree.
Data Source
AI summary
For boosting decompression in the presence of reoccurring Huffman trees, a previous Huffman tree is used to decompress a new data block if a match is identified between a compacted description of the Huffman tree and a recently used Huffman tree compaction.