Self-Seeded Randomizer for Flash Memory Copyback
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Solution Overview
Problem
Internal copyback operations in memory devices face challenges in maintaining data reliability and updating meta-data during data transfer between memory locations within the same die, as traditional methods do not process data and cannot update meta-data effectively, leading to potential reliability and performance issues.
Innovation Solution
The solution involves generating a seed value to scramble host-data and meta-data, separating and encoding them for internal copyback operations, allowing for efficient data transfer and meta-data updating without requiring extensive processing resources, by using a scrambler that decouples the scrambling key from physical addresses and separates meta-data and host-data for independent processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional internal copyback operations are used to transfer data between memory locations, then data transfer efficiency is improved, but data reliability and meta-data updating capability deteriorate
Solution Approach 1:
The patent segments the data transfer process into distinct phases: reading data from source location, processing/scrambling the data, and writing to destination location. This segmentation allows the system to maintain efficiency through internal copyback while incorporating reliability measures like scrambling and meta-data updates at specific stages without compromising the overall transfer speed.
Solution Approach 2:
The patent applies preliminary actions by performing scrambling and meta-data updates during the data transfer process itself, rather than as separate post-processing steps. The scrambler is configured to update meta-data as data is being transferred, ensuring reliability measures are integrated into the efficient copyback operation.
2Reliability
If data scrambling is applied during internal copyback operations, then data reliability is improved, but processing resource utilization increases
Solution Approach 1:
The patent merges the scrambling function with the existing internal copyback operation. The scrambler is integrated into the data path of the copyback mechanism, allowing data to be scrambled and transferred simultaneously through shared hardware resources, thereby improving reliability without proportionally increasing processing complexity.
Solution Approach 2:
The scrambler is designed to perform multiple functions: it scrambles data for reliability, updates meta-data, and operates within the internal copyback framework. This multi-functionality reduces the need for separate dedicated processing units, thereby limiting the increase in device complexity while achieving improved data reliability.
3Manufacturing precision
If meta-data is updated during internal copyback operations, then data management accuracy is improved, but operation latency increases
Solution Approach 1:
The patent ensures continuous useful action by updating meta-data during the data transfer process rather than pausing the copyback operation. The scrambler continuously updates meta-data as data flows through the system, maintaining the continuous nature of the copyback operation while ensuring accurate meta-data management.
Solution Approach 2:
The meta-data updates are performed as a preliminary action integrated into the data path, preparing meta-data information concurrently with data transfer. This approach ensures accurate data management is established before the transfer completes, reducing the need for post-processing and minimizing overall latency.
4Reliability
If seed values are generated and stored with data, then data randomization is improved, but storage space requirements increase
Solution Approach 1:
The patent applies local quality by storing seed values locally with their corresponding data blocks rather than using a centralized seed storage mechanism. Each data block has its own associated seed, allowing for targeted randomization and recovery operations. This approach improves data randomization reliability while limiting storage overhead to only the necessary minimum for each local data unit.
Data Source
AI summary
Disclosed in some examples are methods, systems, devices, and machine-readable mediums that provide for techniques for scrambling and/or updating meta-data that enable an efficient internal copyback operation. In some examples, improved data distribution techniques decouple the scrambling key from a physical address to allow for copyback operations while maintaining data distribution requirements across a memory device. The controller may generate a seed value that is used by a scrambling algorithm to scramble the host-data and meta-data prior to the data being written. The seed value is then encoded and written to the page with encoded versions of the scrambled user data and meta-data—the random seed is written without scrambling the random seed.