Memory Controller Data Hotness Detection for Lower Write Amplification
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Solution Overview
Problem
Existing memory systems struggle to accurately classify data as hot or cold, leading to inefficient data migration, increased write amplification, and reduced service life due to improper handling of cold data during garbage collection.
Innovation Solution
A method for determining data hotness using page table entry region counts and valid data counts to assess data distribution and access frequency, combined with erase/program counts, to accurately classify data as hot or cold, facilitating better data migration and reducing write amplification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If data migration is performed without accurate hotness classification, then data management is simplified, but write amplification increases and service life decreases
Solution Approach 1:
The patent replaces mechanical data management approaches with a computational method that uses page table entry region counts and valid data counts to calculate data hotness metrics. This substitution enables accurate classification without complex hardware mechanisms, resolving the contradiction between management simplicity and service life preservation.
Solution Approach 2:
The patent changes the parameters used for data classification from simple presence/absence to quantitative metrics involving page table entry region counts and valid data counts. This parameter transformation enables precise hotness determination while maintaining management simplicity, thereby extending service life through informed data migration decisions.
2Device complexity
If cold data is not accurately identified, then data classification is simplified, but write amplification increases
Solution Approach 1:
The patent substitutes mechanical data classification with a computational approach using page table entry region counts and valid data counts to determine data hotness. This enables accurate cold data identification without complex classification mechanisms, thereby reducing unnecessary write operations and write amplification.
Solution Approach 2:
The patent implements feedback through continuous monitoring of page table entry region counts and valid data counts to dynamically determine data hotness. This feedback mechanism enables accurate cold data identification and prevents unnecessary write operations, reducing write amplification while maintaining classification simplicity.
3Device complexity
If data hotness is not accurately determined, then data migration is simplified, but performance optimization is limited
Solution Approach 1:
The patent replaces mechanical data migration approaches with a computational method using page table entry region counts and valid data counts to determine data hotness. This enables performance optimization through accurate hotness determination while keeping migration processes simple and efficient.
Solution Approach 2:
The patent transforms data migration from a simple process to an optimized one by introducing quantitative parameters (page table entry region counts, valid data counts) for hotness determination. This parameter enhancement enables performance optimization without increasing migration complexity, as the calculations are performed efficiently during existing memory operations.
Data Source
AI summary
The present disclosure relates to the technical field of data storage, and discloses a method of determining data hotness, a memory controller, and a memory system. The method includes: acquiring a page table entry region count corresponding to a virtual block and a valid data count of the virtual block, wherein the virtual block includes at least one memory block in a memory device; determining a data distribution state of data stored in the virtual block based on the page table entry region count and the valid data count; and determining data hotness of the data stored in the virtual block based on the data distribution state.