Nonvolatile Memory Block Pool Management via Segmented Update Handling
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Solution Overview
Problem
Existing non-volatile flash memory systems face inefficiencies in managing updates, leading to premature aging and high overhead due to inefficient handling of sequential and non-sequential data updates, particularly in handling system control and directory data, which results in excessive garbage collection and block recycling.
Innovation Solution
A non-volatile memory system organizes data into physical groups (metablocks) that can be updated logically, allowing for sequential or chaotic updates, with a management scheme that separates and optimally allocates update blocks based on their usage patterns to minimize consolidations and overhead, enabling concurrent updates and efficient resource use.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a pool of update blocks is managed without separating sequential and non-sequential update patterns, then the block management system is simpler, but garbage collection frequency increases and block aging accelerates
Solution Approach 1:
The patent segments the pool of update blocks into two distinct categories: sequential update blocks and non-sequential update blocks. This segmentation allows the system to apply different management strategies to each type, reducing the frequency of garbage collection operations and minimizing block aging by treating each update pattern according to its specific characteristics rather than using a unified management approach
2Device complexity
If sequential and non-sequential update blocks are managed together, then the management scheme is less complex, but system performance deteriorates due to excessive consolidations
Solution Approach 1:
The patent divides the update block management into separate handling procedures for sequential and non-sequential blocks. Sequential update blocks are managed with assumptions about data placement patterns that reduce consolidation needs, while non-sequential blocks receive different treatment. This segmented approach improves system performance by reducing excessive consolidations that would occur under a unified management scheme
Solution Approach 2:
The patent applies different management qualities and strategies to different types of update blocks based on their local characteristics. Sequential update blocks receive management optimized for sequential write patterns, while non-sequential blocks receive management suited for random access patterns. This local quality approach ensures each block type is handled optimally, preventing performance degradation from inappropriate consolidation operations
3Device complexity
If update blocks are not separated by usage patterns, then allocation is simpler, but premature block aging occurs
Solution Approach 1:
The patent segments update blocks into sequential and non-sequential categories during allocation, enabling the system to track and manage each block's usage pattern independently. This segmentation prevents premature block aging by identifying and preserving blocks with beneficial update patterns while appropriately managing blocks that require more frequent recycling, thereby extending the overall lifespan of the memory blocks
4Device complexity
If a unified approach is used for all update blocks, then the management system is less complex, but overhead increases due to inefficient handling of different update types
Solution Approach 1:
The patent segments the management system into specialized handlers for sequential and non-sequential update blocks. This segmentation reduces system overhead by avoiding unnecessary consolidation operations on blocks where they are not needed, and by applying appropriate management strategies that minimize energy-consuming operations for each block type
Solution Approach 2:
The patent applies locally optimized management strategies to different block types based on their update patterns. Sequential blocks receive management optimized for their write patterns, reducing overhead operations, while non-sequential blocks receive appropriate handling that minimizes unnecessary energy consumption. This local quality approach reduces overall system overhead compared to a unified management approach
Data Source
AI summary
In a nonvolatile memory with block management system, data are written to blocks and are erasable block by block. At any time a pool of blocks are open for storing data concurrently. The number of blocks in the pool is limited. A replacement system allows new blocks to be introduced into the pool without exceeding the limit. In particular, different classes of blocks in the pool each has its own replacement rule, such as closing a least active block before being replaced. In this way, possible inefficiency and premature closure of blocks in the pool can be avoided.