Memory Read Syndrome Comparison for Noise-Induced Error Correction
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Solution Overview
Problem
Memory storage systems face integrity issues due to random telegraph noise, voltage transients, and electromagnetic interference, which can lead to data errors that conventional error control codes struggle to correct, resulting in potential data loss.
Innovation Solution
Implementing a memory system with secondary data extraction capabilities, where memory controllers can read ECC syndromes from multiple devices to identify and correct errors by modifying parameters such as sense amplifier reference values and read window times, and using error correction codes like Hamming codes to enhance data integrity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional error control codes are used, then data integrity is partially protected, but data errors caused by random telegraph noise, voltage transients, and electromagnetic interference cannot be fully corrected
Solution Approach 1:
The patent segments the error correction process into multiple stages: first using conventional ECC codes for basic error correction, then implementing a secondary extraction mechanism that reads ECC syndromes from multiple devices to identify and correct remaining errors that the first stage missed
Solution Approach 2:
The patent introduces an intermediary secondary data extraction mechanism that acts as a bridge between the memory devices and the conventional ECC system. This intermediary reads and analyzes ECC syndromes from multiple devices to identify patterns and correct errors that conventional single-device ECC cannot handle
2Reliability
If memory controllers read ECC syndromes from multiple devices to identify errors, then error correction capability is improved, but system complexity increases
Solution Approach 1:
The memory controller is designed with multi-functionality, serving both as a conventional ECC controller and as a secondary extraction mechanism that reads and analyzes syndromes from multiple devices. This universal design avoids adding separate dedicated hardware for error analysis
Solution Approach 2:
The patent merges the secondary extraction functionality with the existing memory controller architecture, combining the syndrome reading, error pattern analysis, and correction coordination functions into a unified control structure rather than implementing them as separate independent systems
3Measurement precision
If parameters such as sense amplifier reference values and read window times are modified, then error correction effectiveness is improved, but control complexity increases
Solution Approach 1:
The patent implements dynamic adjustment of read parameters based on error patterns detected during secondary extraction. The memory controller modifies sense amplifier reference values and read window times adaptively according to the specific error conditions identified, rather than using fixed parameters
Solution Approach 2:
The system employs feedback mechanisms where the secondary extraction process analyzes ECC syndromes from multiple devices, identifies error patterns, and uses this information to adjust read parameters for subsequent operations. This closed-loop feedback enables continuous improvement of error detection and correction effectiveness
Data Source
AI summary
A method includes calculating a first syndrome of a codeword read from a memory location under a first set of conditions and calculating a second syndrome of the codeword read from the memory location under a second set of conditions. The method also includes analyzing the first and second syndromes and applying one of the first and second syndromes to the codeword to find the codeword having a minimum number of errors.