Memory Block Garbage Collection via Obsolescence Pattern Segmentation
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Solution Overview
Problem
Existing memory systems inefficiently perform garbage collection by mixing different data types, such as random and sequential data, leading to inefficient operations and loss of initial data segregation over time, as they primarily rely on the amount of valid data rather than obsolescence patterns.
Innovation Solution
A memory system and method that classify blocks based on their obsolescence patterns, using a bitmap to determine the locations of invalid areas and assign types to blocks, allowing garbage collection to be performed only on blocks with similar patterns, thereby separating valid data from different types into different target blocks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If garbage collection is performed on blocks with the lowest valid count regardless of data type, then the number of garbage collection operations increases, but the efficiency of garbage collection decreases due to mixing different data types
Solution Approach 1:
The patent segments blocks into different types (sequential blocks and random blocks) based on their data characteristics and obsolescence patterns. This segmentation allows the garbage collection process to treat different block types differently, improving efficiency by avoiding the mixing of sequential and random data in the same target block.
Solution Approach 2:
The patent dynamically determines block types by analyzing the obsolescence patterns of valid data in blocks. Blocks are not statically assigned types but are dynamically classified based on their current state, allowing the system to adapt to changing data patterns and optimize garbage collection accordingly.
2Loss of substance
If sequential and random data are mixed in the same block, then initial data segregation is lost, but the amount of data to be copied during garbage collection increases
Solution Approach 1:
The patent segments blocks into sequential blocks and random blocks based on their data characteristics. Sequential blocks contain mostly sequential data while random blocks contain mostly random data. This segmentation preserves data type separation and reduces the amount of data that needs to be copied during garbage collection by targeting only the appropriate block types.
Solution Approach 2:
The patent changes the parameter used for block selection from单纯的valid count to a combination of block type and obsolescence pattern. This parameter change allows the system to maintain data type separation while optimizing the garbage collection process.
3Reliability
If blocks are classified and garbage collection is performed only on similar obsolescence patterns, then data type separation is maintained, but the classification process adds system complexity
Solution Approach 1:
The system performs self-service by automatically analyzing the obsolescence patterns of valid data in blocks and determining block types without external intervention. The controller autonomously classifies blocks and manages the garbage collection process, reducing the need for complex external classification mechanisms.
Data Source
AI summary
A memory system and method are provided for performing garbage collection on blocks based on their obsolescence patterns. In one embodiment, a controller of a memory system classifies each of the plurality of blocks based on its obsolescence pattern and performs garbage collection only on blocks classified with similar obsolescence patterns. Other embodiments are possible, and each of the embodiments can be used alone or together in combination.