Memory Data Sequentialization for Fragmented LBA Defragmentation
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Solution Overview
Problem
Existing technologies face challenges in efficiently managing fragmented data storage in memory systems, leading to inefficiencies in data access and performance.
Innovation Solution
A memory system initiates a data optimization operation to identify and sequentialize non-sequential logical block addresses (LBAs) to defragment the data, reducing signaling and improving performance by optimizing logical-to-physical (L2P) table compression and granularity adjustment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data is stored in non-sequential physical block addresses to optimize write performance and utilization, then storage efficiency is improved, but data fragmentation occurs leading to increased access latency
Solution Approach 1:
The patent segments the data storage management into two independent layers: logical block address (LBA) management handled by the host system and physical block address (PBA) management handled by the memory system. This segmentation allows the host to generate sequential LBAs while the memory system independently maps them to non-sequential PBAs for optimized storage, resolving the contradiction between write performance and access latency by decoupling the two functions.
Solution Approach 2:
The patent introduces an L2P (Logical-to-Physical) table as an intermediary data structure that bridges the gap between sequential LBAs and non-sequential PBAs. This L2P table acts as a mediator that enables efficient translation and random access to fragmented data, allowing the system to maintain both high write performance through non-sequential PBA allocation and low access latency through direct LBA-to-PBA mapping.
2Speed
If host system performs data defragmentation to improve access speed, then data access performance is improved, but signaling overhead and processing complexity increase
Solution Approach 1:
The patent implements self-service by enabling the memory system to autonomously manage data placement and fragmentation without requiring host system intervention. The memory system controller independently performs L2P table updates, data redistribution, and optimization operations, eliminating the need for host system defragmentation commands and reducing signaling overhead while maintaining fast data access speeds.
Solution Approach 2:
The patent applies preliminary action by pre-allocating and pre-organizing data in the memory system using sequential LBA mapping before actual write operations occur. The L2P table is proactively maintained and updated during normal operations, so that data is already optimized for access before defragmentation is needed, reducing the need for complex post-write processing and signaling.
3Measurement precision
If L2P table is maintained with high granularity for precise tracking, then data location accuracy is improved, but memory usage and processing overhead increase
Solution Approach 1:
The patent implements dynamic L2P table management where the granularity and detail of tracking are adjusted based on operational needs. The system can dynamically switch between fine-grained tracking (for precision data location) and coarser-grained tracking (for reduced memory usage), allowing flexible adaptation to different workload requirements and optimizing the balance between data location accuracy and memory consumption.
Solution Approach 2:
The patent applies parameter changes by modifying the L2P table structure and tracking granularity based on data access patterns and system state. The system can change parameters such as entry size, update frequency, and compression level of the L2P table to optimize the trade-off between data location precision and memory resource consumption, using fine-grained tracking when needed and coarser tracking when memory is constrained.
Data Source
AI summary
In accordance with examples as described herein, a memory system may initialize a data optimization operation by transmitting signaling to a host system. For example, the memory system may identify data associated with non-sequential logical block addresses (LBAs), and may indicate the discontinuous LBAs to the host system. In response, the host system may indicate which of the discontinuous LBAs represent sequential data. Accordingly, the memory system may sequentialize the one or more of the discontinuous LBAs to defragment the associated data.