Garbage Collection Efficiency in NAND Memory via Two-Table Architecture
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Solution Overview
Problem
Traditional flash translation layers (FTLs) in NAND memory devices face inefficiencies in garbage collection due to the need to search and load entire logical to physical (L2P) mapping tables, which is time-consuming and resource-intensive, especially when RAM resources are limited.
Innovation Solution
Implementing a two-table architecture with a region validity counter table (RVCT) and a region validity bitmap table (RVBT) to efficiently manage garbage collection by tracking valid pages and identifying regions involved in garbage collection, reducing the need to load non-useful regions and improving search efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional FTL searches and loads entire L2P mapping tables for garbage collection, then complete mapping information is available for accurate garbage collection, but time consumption and resource usage increase significantly
Solution Approach 1:
The patent extracts only the necessary portion of L2P mapping table (specifically the region validity bitmap indicating which regions contain valid pages) rather than loading the entire mapping table. This selective extraction of critical information enables the garbage collection process to identify candidate blocks without the overhead of processing complete mapping data, thus reducing time consumption while maintaining garbage collection accuracy.
Solution Approach 2:
The L2P mapping table is segmented into multiple regions, and the patent introduces a region validity bitmap that tracks the status of each region separately. This segmentation allows the garbage collection process to operate on a region-by-region basis, loading only those regions that contain valid pages, thereby significantly reducing the time and resources required compared to loading the entire mapping table at once.
2Ease of operation
If traditional FTL loads entire L2P mapping tables into RAM, then complete mapping data is available for processing, but RAM resource consumption increases
Solution Approach 1:
The patent extracts only the essential metadata (region validity bitmap) that indicates which regions contain valid pages, rather than loading the entire L2P mapping table into RAM. This selective extraction dramatically reduces RAM resource consumption while maintaining the ability to perform garbage collection operations by accessing only the necessary regions on-demand.
Solution Approach 2:
The mapping table is divided into multiple regions with separate validity tracking. This segmentation enables the system to load only the specific regions that contain valid pages into RAM during garbage collection, rather than pre-loading the entire mapping table, thus optimizing RAM resource usage while preserving mapping table accessibility for processing.
3Reliability
If the system processes entire L2P mapping tables during garbage collection, then all valid pages can be identified, but processing overhead and latency increase
Solution Approach 1:
The patent extracts the region validity bitmap that concisely indicates which regions contain valid pages, enabling the garbage collection process to identify candidate blocks without processing the entire L2P mapping table. This extraction maintains reliability by ensuring all regions with valid pages are identified, while significantly improving productivity by reducing the processing overhead associated with handling complete mapping data.
Solution Approach 2:
The L2P mapping table is segmented into multiple regions with individual validity tracking. This segmentation allows the garbage collection process to efficiently identify and process only those regions that contain valid pages, rather than uniformly processing the entire mapping table. The result is improved garbage collection efficiency through reduced processing overhead, while maintaining complete identification of valid pages across all regions.
Data Source
AI summary
A variety of applications can include apparatus and/or methods of operating the apparatus in which storage in the memory device is managed. An allocation can include conducting a garbage collection procedure to free up one or more blocks. In various embodiments, execution of a garbage collection procedure can be based on operation of two tables with respect to a logical to physical mapping table split into logical to physical mapping table regions saved in the memory device. The first table can maintain counts of valid pages in blocks for a logical to physical mapping table region. The second table can include bits to identify logical to physical mapping table regions involved in the garbage collection procedure based on the entries in the first table. Search of the second table can determine logical to physical mapping table regions involved in the garbage collection. Additional apparatus, systems, and methods are disclosed.