Data Word Syndrome Staging for Low-Energy Error Correction
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Solution Overview
Problem
Existing methods for error recognition and correction in data words are inefficient in terms of performance and energy consumption, as they often require full syndrome computation for every data word, which is unnecessary for error-free data words.
Innovation Solution
A method where a first syndrome of a first code is determined for a data word, and if an error is recognized, a second syndrome of a second code is computed, which includes the components of the first syndrome, allowing for partial syndrome computation and reducing computational resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If full syndrome computation is performed for every data word, then error recognition and correction capability is ensured, but energy consumption and processing time increase
Solution Approach 1:
The patent applies partial action by computing only a first syndrome using a first code (with fewer syndrome components) for all data words, and only computing the complete second syndrome using the second code when the first syndrome indicates an error. This partial computation approach reduces energy consumption for error-free data words while maintaining full error correction capability when needed.
2Reliability
If full syndrome computation is performed for every data word, then error recognition and correction capability is ensured, but processing time increases
Solution Approach 1:
The patent implements partial action by performing only partial syndrome computation (first syndrome with fewer components) for all incoming data words, and completing the full syndrome computation (second syndrome) only when errors are detected. This significantly reduces average processing time while maintaining the ability to correct errors when they occur.
Solution Approach 2:
The patent segments the syndrome computation process into two stages: a fast first syndrome computation using a first code for initial error detection, and a complete second syndrome computation using a second code only when needed. This segmentation allows the system to handle the common case (error-free data) quickly while preserving full error correction capability for rare error cases.
3Use of energy by moving object
If partial syndrome computation is performed, then energy consumption and processing time are reduced, but error detection capability may be compromised
Solution Approach 1:
The patent applies the nested doll principle by designing the first code and second code such that the first code is contained within the second code. The parity check matrix of the first code is a submatrix of the parity check matrix of the second code, and the first syndrome components are a subset of the second syndrome components. This nesting ensures that the partial first syndrome computation does not compromise error detection capability, as the complete second syndrome (which includes all first syndrome components) can be computed when needed.
Solution Approach 2:
The patent uses partial action with a carefully designed first code that, while using fewer syndrome components, maintains sufficient error detection capability to identify when full syndrome computation is needed. The first code is designed to detect errors with high probability, triggering complete syndrome computation only when necessary, thus balancing energy efficiency with reliable error detection.
Data Source
AI summary
An approach for processing a data word in which a data word is received, in which a first syndrome of a first code is determined, the first syndrome having components, and in which a second syndrome of a second code is determined when the syndrome of the first code recognizes an error, the second syndrome comprising the components of the first syndrome.