Bias Calculation Circuit for Faster Storage Device Characterization
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Solution Overview
Problem
The existing methods for characterizing storage devices are time-consuming and costly due to the need for a long period of testing to determine if they meet quality criteria, which involves a small number of failures.
Innovation Solution
The implementation of data processing circuits with a data detector and bias calculation circuit that apply data detection algorithms to generate soft decision data and calculate bias values, allowing for predictable error rate increase and faster characterization by degrading circuit operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional testing methods are used to characterize storage devices, then measurement precision is maintained, but loss of time increases significantly
Solution Approach 1:
The patent applies preliminary action by pre-calculating bias values that represent the difference in error rates between two data sets before actual device characterization. These bias values are computed offline and stored for later use, allowing the system to skip lengthy traditional testing while maintaining characterization accuracy. The bias calculation circuit pre-processes reference data to create lookup tables that can be quickly applied during device evaluation.
Solution Approach 2:
The patent uses copying by creating a simplified model of the device under test through a virtual reference device. Instead of physically testing the actual device for extended periods, the system generates soft decision data from a virtual reference that replicates the device's error characteristics. This virtual copy allows rapid characterization by simulating long-term behavior without the time cost of actual extended testing.
2Reliability
If traditional testing methods are used to characterize storage devices, then reliability of characterization is maintained, but productivity decreases due to long testing periods
Solution Approach 1:
The patent replaces the mechanical testing system with a computational model. Instead of physically operating the device for extended periods to generate failure data, the system uses a data processing circuit with histogram calculation circuits and bias calculation circuits that computationally model device behavior. This substitution maintains reliability by preserving the statistical relationships in the data while dramatically improving productivity through faster computation than physical testing.
3Loss of time
If bias calculation circuits are added to generate predictable degradation, then loss of time is reduced, but device complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the bias calculation function into separate, modular circuit components. The data processing circuit is segmented into a histogram calculation circuit that processes soft decision data, a normalization circuit that scales the histograms, and a bias calculation circuit that computes the differential bias values. This modular segmentation allows each component to be optimized independently and simplifies integration, reducing the overall complexity burden despite adding functionality.
Solution Approach 2:
The bias calculation circuit performs multiple functions: it calculates histograms of soft decision data, normalizes these histograms, computes differential bias between reference and actual device behavior, and generates lookup tables for error injection. This multi-functionality consolidates what would otherwise require separate circuits into a single versatile module, minimizing the increase in device complexity while maximizing the time-saving benefits.
Data Source
AI summary
Various embodiments of the present invention provide systems and methods for data processing. As an example, a data processing circuit is disclosed that includes a data detector circuit and a bias calculation circuit. The data detector circuit is operable to apply a data detection algorithm to a first data set to yield a first series of soft decision data, and to apply the data detection algorithm to a second data set to yield a second series of soft decision data. The bias calculation circuit operable to calculate a series of bias values based at least in part on the first series of soft decision data and the second series of soft decision data. The series of bias values correspond to a conversion between the first series of soft decision data and the second series of soft decision data.