Memory Controller Realignment Using Minimum Syndrome Weight
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing memory devices face data misalignment issues due to small changes in error correction code (ECC) words, rendering them undecodable, particularly in structured data, and conventional approaches require specific content structures, making them unsuitable for both structured and unstructured data.
Innovation Solution
A memory controller system that scans skewed codewords by inserting or removing bits at different locations to determine the smallest syndrome weight, allowing for data realignment and decoding, regardless of data structure, using a memory interface and controller circuit configured to receive, scan, and decode skewed codewords.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional data alignment approaches are used, then structured data can be corrected, but unstructured data cannot be processed
Solution Approach 1:
The patent changes the approach from structure-based correction to syndrome-weight-based correction. Instead of relying on data having a specific structure, the system evaluates all possible alignments by computing syndrome weights and selects the alignment with the minimum syndrome weight. This parameter change makes the system adaptable to both structured and unstructured data while ensuring decodability.
2Reliability
If ECC word size is strictly structured, then error correction is reliable, but small changes cause misalignment and undecodability
Solution Approach 1:
The patent performs preliminary alignment correction before the main ECC decoding process. By scanning through all possible bit insertions/deletions and computing syndrome weights in advance, the system identifies the correct alignment offset. This preliminary action prevents misalignment from causing decoding failures, maintaining reliability while managing complexity through a systematic search approach.
3Reliability
If data misalignment is detected, then undecodable data can be corrected, but the correction process requires specific content structure
Solution Approach 1:
The patent creates a universal alignment correction mechanism that works for both structured and unstructured data. The syndrome weight computation and minimum-weight selection process is a general-purpose method that does not depend on data content or structure. This universal approach ensures data recoverability across all data types while eliminating content structure requirements.
Data Source
AI summary
A memory controller that includes, in one implementation, a memory interface and a controller circuit. The memory interface is configured to interface with a non-volatile memory. The controller circuit is configured to receive a skewed codeword read from the non-volatile memory. The controller circuit is also configured to scan the skewed codeword by inserting or removing a quantity of bits at different locations in the skewed codeword and determining resulting syndrome weights of the skewed codeword. The controller circuit is further configured to determine an adjusted codeword by inserting or removing the quantity of bits at one of the different locations in the skewed codeword which results in a smallest syndrome weight. The controller circuit is also configured to decode the adjusted codeword.