Scaled Memory Error Reporting via Thresholded Count Compression

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Solution Overview

Problem

Existing memory devices face challenges in efficiently storing and reporting error counts due to the large storage space required for high-granularity metadata, which can grow significantly over the device's lifespan, necessitating a more efficient method to convey reliability and lifespan information with reduced storage requirements.

Innovation Solution

Implementing a scaling algorithm to convert raw error counts into scaled error counts using histogram bins, either linearly or logarithmically, and storing these scaled counts in user-accessible mode registers for reporting, allowing for reduced storage needs while maintaining valuable performance insights.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If high-granularity error count metadata is stored to maintain measurement precision, then error monitoring accuracy is improved, but storage space requirements increase significantly

Engineering Contradiction:

Improveerror count monitoring accuracyVSAvoidstorage space

Core Design Contradiction:

Measurement precisionVSArea of stationary object

Solution Approach 1:

The patent applies parameter changes by transforming the error count data from its original high-precision format into a scaled-down representation. The error count is divided by a scaling factor (e.g., 10, 100, or 1000) and rounded to the nearest integer, fundamentally changing the parameter representation to reduce storage requirements while maintaining sufficient monitoring accuracy for reliability assessments.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent extracts only the essential information needed for reliability monitoring from the complete error count metadata. By taking out the most significant portion of the data (the scaled error count) and discarding the less critical detailed breakdown, the system achieves adequate monitoring capability with minimal storage overhead.

Inventive Principle:

Principle #2Taking out (Extraction)

2Loss of information

If detailed raw error count data is stored to maintain information availability, then reliability assessment accuracy is improved, but device complexity increases

Engineering Contradiction:

Improvereliability information availabilityVSAvoidmetadata management complexity

Core Design Contradiction:

Loss of informationVSDevice complexity

Solution Approach 1:

The patent extracts only the essential reliability information from the complete error count dataset. By taking out the scaled error count that captures the most critical reliability trends and discarding the detailed raw data, the system maintains sufficient reliability assessment capability while significantly simplifying data management complexity.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The patent uses a simplified, scaled representation of error counts that can be easily stored and managed, replacing the complex raw data structures. This disposable-like approach uses minimal resources to convey the essential reliability information without the burden of managing comprehensive detailed records.

Inventive Principle:

Principle #27Cheap short-living objects (Disposable)

Data Source

PatentUS20260003731A1Methods for error count reporting with scaled error count information, and memory devices employing the same

Publication Date: 2026.01.01 LODESTAR LICENSING GROUP LLC

AI summary

An apparatus comprising a memory array including a plurality of memory cells arranged in a plurality of columns and a plurality of rows is provided. The apparatus further comprises circuitry configured to perform an error detection operation on the memory array to determine a raw count of detected errors, to compare the raw count of detected errors to a threshold value to determine an over-threshold amount, to scale the over-threshold amount according to a scaling algorithm to determine a scaled error count, and to store the scaled error count in a user-accessible storage location.