Gate Aware Iterative Data Processing for Accuracy and Speed
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Solution Overview
Problem
Data processing circuits often require multiple iterations through data detector and decoder circuits to recover original data, with default processing sometimes yielding incorrect results, highlighting a need for advanced scheduling methods to improve efficiency and accuracy.
Innovation Solution
The implementation of a data processing system that applies a data detection algorithm and repeatedly applies a data decoding algorithm, with the number of passes determined by a read gate signal, allowing for variable local and global iterations based on data quality and availability, and utilizing a gate-based scheduler to idle circuits when data is not received, thereby optimizing bandwidth usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple iterations are performed through data detector and decoder circuits to recover original data, then data recovery accuracy is improved, but processing time and computational complexity increase
Solution Approach 1:
The patent implements dynamic adjustment of the number of iterations based on data quality metrics. The system monitors convergence criteria and automatically determines when sufficient iterations have been performed, allowing the iteration count to vary rather than remaining fixed. This resolves the contradiction by adapting processing depth to actual data recovery needs, avoiding both premature termination and excessive computation.
Solution Approach 2:
The system incorporates feedback mechanisms where the output of the data decoder is fed back to the data detector, and convergence status is monitored and reported back to control the iteration process. This feedback loop enables the system to adjust the number of iterations based on actual progress, ensuring sufficient accuracy when needed while stopping when convergence is achieved, thus balancing accuracy and time requirements.
2Productivity
If a fixed default number of iterations is used for data processing, then processing speed is maintained, but data recovery accuracy deteriorates for difficult data
Solution Approach 1:
The patent transitions from a fixed iteration count to a dynamic, data-quality-dependent iteration count. The system evaluates data characteristics and convergence progress in real-time, adjusting the number of iterations accordingly. This allows the system to maintain fast processing for easy data while allocating additional iterations only when necessary for difficult data, resolving the contradiction between speed and accuracy.
Solution Approach 2:
The system changes the parameter of iteration count based on data quality metrics and convergence status. Rather than using a constant default value, the iteration parameter is adapted according to actual processing conditions. This parameter change enables the system to optimize both speed and accuracy by matching the processing depth to the actual difficulty of the data being processed.
3Measurement precision
If the number of iterations is increased to improve data recovery, then accuracy is improved, but resource utilization and processing efficiency deteriorate
Solution Approach 1:
The patent implements dynamic iteration control that adjusts processing depth based on real-time convergence assessment. The system continuously monitors whether additional iterations are likely to improve accuracy significantly and only allocates resources for extra iterations when necessary. This dynamic approach optimizes the balance between accuracy and efficiency by avoiding unnecessary computational resources on already-converged data.
Solution Approach 2:
The feedback mechanism monitors convergence criteria and provides real-time information about processing progress. This feedback enables the system to make informed decisions about resource allocation, stopping iterations when convergence is achieved and avoiding wasted computational resources on data that has already been sufficiently processed, thus optimizing both accuracy and efficiency.
Data Source
AI summary
The present inventions are related to systems and methods for iterative data processing scheduling. In one case a data processing system is disclosed that includes a data detector circuit and a data decoder circuit. The data detector circuit is operable to apply a data detection algorithm to a data set to yield a detected output. The data decoder circuit is operable to repeatedly apply a data decoding algorithm to the detected output to yield a decoded output over a number of passes, where the number of passes is within an allowable number of local iterations selected based at least in part on a read gate signal.