Folded Parity Sector Decoding for Low-Latency Error Correction
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Solution Overview
Problem
Existing data processing systems face challenges in efficiently correcting errors in digital data due to the limitations of traditional error checking systems, which can lead to data corruption and reduced effectiveness in data transfer and storage.
Innovation Solution
The implementation of folded parity sector processing, which generates parity bits by combining multiple user data sectors using XOR operations, allowing for error correction and decoding across multiple columns, thereby sharing parity protection between good and bad codewords.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional error checking systems are used, then data transfer and storage can be performed, but error correction capabilities are insufficient leading to data corruption
Solution Approach 1:
The patent divides the data block into multiple sectors and generates separate parity sectors for different groups of sectors. This segmentation allows error correction to be performed independently on different data groups, improving reliability without requiring a single complex global parity calculation across all data.
Solution Approach 2:
The patent introduces a folded parity sector that wraps around multiple columns of data sectors, adding a dimensional aspect to error correction. Instead of only horizontal parity checks across sectors, the folded parity creates vertical and diagonal check patterns, enabling more efficient error detection and correction with reduced computational complexity.
2Reliability
If more data sectors are grouped together for parity protection, then error correction coverage is improved, but buffer requirements increase
Solution Approach 1:
The patent divides the data block into multiple smaller sectors with individual parity protection, rather than treating the entire data block as one unit. This allows error correction to be performed on smaller independent groups, reducing the buffer memory needed to hold all data and parity information simultaneously while maintaining comprehensive error correction coverage.
Solution Approach 2:
The folded parity sector provides redundant protection by checking data from multiple columns, offering more than minimal error correction capability. This partial redundancy approach improves reliability for high-error scenarios while keeping the buffer requirements manageable by not requiring full duplication of all data sectors.
3Reliability
If decoding is performed on all codewords simultaneously, then error correction is comprehensive, but decoding latency increases
Solution Approach 1:
The patent organizes data into multiple independently decodable codewords with their own parity sectors. This allows the decoder to process multiple codewords in parallel rather than sequentially, reducing overall decoding latency while maintaining comprehensive error correction across the entire data block.
Solution Approach 2:
The folded parity sector structure enables a two-dimensional decoding approach where parity checks can be performed across rows and columns simultaneously. This dimensional organization allows for parallel processing of multiple codewords and their corresponding folded parity sectors, reducing decoding latency while ensuring complete error correction coverage.
Data Source
AI summary
An apparatus for processing data includes a decoder configured to iteratively decode codewords in a data block representing a number of user data sectors, the codewords including user data, folded parity sector data and error correction code parity bits. The folded parity sector data includes a number of parity checks, each with multiple user data bits from each of the data sectors, and with an offset between each of the user data bits from the data sectors determined at least in part by a number of folds in the data sectors. The apparatus also includes a scheduler configured to control decoding of the codewords based at least in part on the folded parity sector data.