Biased Sampling for Memory Wear Leveling

Solution Overview

Problem

Conventional memory sub-systems face high latency and increased computational overhead due to the need to sort and manage large lists of data units for wear leveling, which is exacerbated by the limited endurance of non-volatile memory components.

Innovation Solution

Implementing a biased sampling methodology to select and sort a subset of data units based on wear metrics, reducing the need to manage all data units and thereby minimizing processing and memory resources, allowing for efficient wear leveling operations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If conventional wear leveling sorts and manages large lists of all data units, then wear distribution is improved, but latency and computational overhead increase

Engineering Contradiction:

Improvewear distributionVSAvoidlatency

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The patent divides the large set of all data units into multiple smaller subsets or groups. Instead of sorting and managing all data units globally, the system performs wear leveling operations on individual subsets independently. This segmentation reduces the computational complexity and time required for each sorting operation, thereby reducing latency while still achieving wear distribution across the entire memory space through coordinated subset management.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent applies wear leveling operations to only a partial set of data units (a subset) rather than all data units. By selecting and processing only the most worn or most frequently accessed data units in each operation cycle, the system achieves sufficient wear distribution without the computational overhead of sorting and managing the complete set of all data units, thus reducing latency and computational overhead.

Inventive Principle:

Principle #16Partial or excessive action

2Reliability

If conventional wear leveling sorts and manages large lists of all data units, then wear distribution is improved, but computational overhead increases

Engineering Contradiction:

Improvewear distributionVSAvoidcomputational overhead

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent divides the large set of all data units into multiple smaller subsets or groups. Instead of sorting and managing all data units globally, the system performs wear leveling operations on individual subsets independently. This segmentation reduces the computational complexity and time required for each sorting operation, thereby reducing latency while still achieving wear distribution across the entire memory space through coordinated subset management.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent applies wear leveling operations to only a partial set of data units (a subset) rather than all data units. By selecting and processing only the most worn or most frequently accessed data units in each operation cycle, the system achieves sufficient wear distribution without the computational overhead of sorting and managing the complete set of all data units, thus reducing latency and computational overhead.

Inventive Principle:

Principle #16Partial or excessive action

3Productivity

If biased sampling selects only a subset of data units, then latency and resource usage are reduced, but wear distribution effectiveness may be compromised

Engineering Contradiction:

Improvewear leveling efficiencyVSAvoidwear distribution effectiveness

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The patent applies different sampling strategies or selection criteria to different subsets of data units based on their local characteristics. Instead of using a uniform approach, the system identifies and processes subsets with specific wear patterns or access patterns using targeted sampling methods. This local quality approach ensures that each subset receives appropriate wear leveling attention, maintaining effectiveness while reducing overall computational burden through selective processing.

Inventive Principle:

Principle #3Local quality

Data Source

PatentUS11341036B2Biased sampling methodology for wear leveling

Publication Date: 2022.05.24 MICRON TECHNOLOGY INC

AI summary

A system includes a memory device and a processing device, coupled to the memory device. The processing device is to sample a first subset of data units from a set of data units of the memory device using a biased sampling process that increases a probability of sampling particular data units from the set of data units based on one or more characteristics associated with the particular data units. The processing device is to identify a first candidate data unit from the first subset of data units and perform a wear leveling operation in view of the first candidate data unit.