Memory Block Segmentation for Hot and Cold Data Migration
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Solution Overview
Problem
Existing memory systems face complexity and performance deterioration issues, leading to inefficiencies in data processing and storage, particularly in portable electronic devices where stability, durability, and low power consumption are crucial.
Innovation Solution
A memory system that divides memory blocks into groups, classifies user data and meta data based on type information, and migrates segments based on read counts, utilizing Multi Level Cell (MLC), Triple Level Cell (TLC), and Single Level Cell (SLC) memory blocks to optimize storage and retrieval operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If memory blocks are divided into groups and data is classified and migrated based on read counts, then data access efficiency is improved, but system complexity increases
Solution Approach 1:
The memory device is divided into multiple memory blocks organized into first and second groups. The controller classifies user data into different types (first type, second type, third type, fourth type) based on read counts and access patterns. This segmentation allows differentiated management of hot and cold data, improving access efficiency while maintaining manageable complexity through systematic organization.
Solution Approach 2:
The system dynamically migrates data between memory blocks based on changing read counts and access patterns. Data that transitions from cold to hot (increasing read counts) is migrated from first group blocks to second group blocks, and vice versa. This dynamic adaptation allows the system to optimize performance based on actual usage patterns without requiring static pre-configuration.
2Productivity
If data is migrated between different memory block types (SLC, MLC, TLC), then storage performance is optimized, but control complexity increases
Solution Approach 1:
Different memory block types (SLC, MLC, TLC) are assigned to different groups based on their characteristics. SLC blocks with higher endurance are placed in the first group for hot data requiring frequent updates, while TLC blocks are placed in the second group for cold data. This local quality assignment matches data access patterns with appropriate storage media characteristics, optimizing performance while simplifying control through rule-based migration.
3Productivity
If segments are classified into multiple types based on read count, then data management efficiency is improved, but processing complexity increases
Solution Approach 1:
The system uses read count as a dynamic parameter to classify data segments into different types. First type segments have low read counts (cold data), while third type segments have high read counts (hot data). This parameter-based classification enables automated migration decisions and differentiated management strategies, improving data management efficiency through objective, measurable criteria rather than subjective judgment.
Data Source
AI summary
A memory system may include: a memory device comprising a plurality of pages, which include a plurality of memory cells coupled to a plurality of word lines, and in which data is stored, and a plurality of memory blocks in which the pages are included; and a controller configured to divide the memory blocks into a first group and a second group, perform a command operation corresponding to a command received from a host, and respectively store segments of user data and meta data for the command operation in memory blocks included in the first group or memory blocks included in the second group, in accordance with type information of the user data Included in the command.