Host-Side Codeword Error Classification Using Multi-Bit Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing memory systems struggle to comprehensively classify various types of errors that can occur in stored codewords, limiting their ability to determine error status effectively, especially in higher-reliability systems.
Innovation Solution
A system that includes a host device and a memory device, where the memory device generates two or more error detection bits to indicate the error status of a codeword, and the host device receives these bits to determine the error status, enabling classification of correctable and uncorrectable errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional error detection methods are used in memory systems, then the system structure remains simple, but the ability to comprehensively classify various types of errors is insufficient
Solution Approach 1:
The patent segments error detection into multiple independent detection bits, each responsible for detecting specific error types (e.g., first detection bit for error type A, second detection bit for error type B). This segmentation enables comprehensive error classification while keeping each detection component relatively simple and modular.
Solution Approach 2:
The patent transitions from traditional single-bit error detection to multi-dimensional error detection by introducing multiple detection bits that operate in different detection dimensions. Each detection bit provides error information from a different perspective, enabling more comprehensive error classification without proportionally increasing overall system complexity.
2Measurement precision
If multiple error detection bits are generated to classify error types, then error status determination accuracy improves, but the quantity of data to be processed increases
Solution Approach 1:
The patent extracts only the essential error status information from multiple detection bits rather than processing all raw detection data. By taking out only the critical error classification information needed for decision-making, the system achieves accurate error status determination while minimizing unnecessary data processing overhead.
Solution Approach 2:
The patent implements partial error detection action by using multiple detection bits that focus on detecting specific critical error types rather than attempting to detect and process all possible error conditions. This partial action approach provides sufficient error classification accuracy for practical applications without the excessive processing burden of comprehensive error analysis.
3Reliability
If comprehensive error classification is implemented, then system reliability improves, but the complexity of error handling logic increases
Solution Approach 1:
The patent applies local quality by assigning specific detection functions to different detection bits, where each bit is optimized for detecting particular error types. This localized specialization enables comprehensive error classification while keeping the handling logic for each error type relatively simple and manageable.
Solution Approach 2:
The patent performs preliminary error classification by generating multiple detection bits that pre-categorize error types before the main error handling logic is executed. This preliminary action organizes error information in advance, reducing the complexity of subsequent error handling decisions and improving overall system reliability.
Data Source
AI summary
Methods, systems, and devices for error detection and classification at a host device are described. A host device may communicate a read command for a codeword stored at a memory device. In response to communicating the read command, the host device may receive the codeword and an error indication bit that indicates whether the memory device detected an error in the codeword. The host device may use the codeword to generate a set of syndrome bits. The host device may determine an error status of the codeword based on the error indication bit for the codeword and the set of syndrome bits for the codeword.