Session Tables for Predictive L2P Cache Loading
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Solution Overview
Problem
Memory systems experience increased address translation latency due to the need to wait for access commands before loading logical-to-physical (L2P) tables into cache, which negatively impacts system performance.
Innovation Solution
Implementing session tables to predictively load L2P tables into cache by identifying sets of numerically sequential logical block addresses likely to be accessed, thereby reducing address translation latency and improving system performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If L2P tables are loaded into cache only after receiving access commands, then cache memory is not wasted on premature loading, but address translation latency increases due to waiting for commands
Solution Approach 1:
The patent implements session tables that predictively identify sets of numerically sequential logical block addresses likely to be accessed and loads corresponding L2P tables into cache before actual access commands are received. This preliminary loading action resolves the contradiction by eliminating the waiting time for address translation while avoiding wasteful cache usage through intelligent prediction based on sequential access patterns.
2Loss of time
If session tables are used to predictively load L2P tables, then address translation latency is reduced, but device complexity increases due to additional table management
Solution Approach 1:
Session tables are implemented to perform preliminary identification of likely accessed L2P tables based on sequential logical block address patterns. This allows the system to proactively load necessary L2P tables into cache before access commands arrive, reducing address translation latency while managing complexity through pattern-based prediction rather than complex real-time decision-making.
Solution Approach 2:
The session table acts as an intermediary layer between the access command interface and the L2P table cache management. It receives access patterns, predicts future needs based on sequential address relationships, and triggers L2P table loading accordingly. This intermediary simplifies the overall system by centralizing the prediction and loading logic in a dedicated component.
Data Source
AI summary
Methods, systems, and devices for session-based memory operation are described. A memory system may determine that a logical address targeted by a read command is associated with a session table. The memory system may write the session table to a cache based on the logical address being associated with the session table. After writing the session table to the cache, the memory system may use the session table to determine one or more logical-to-physical (L2P) tables and write the one or more L2P tables to the cache. The memory system may use the L2L tables to perform address translation for logical addresses.