NAND Flash Row-Based Programming Parameter Optimization
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Solution Overview
Problem
Traditional Program Digital Signal Processing (DSP) methods for NAND flash memory devices achieve high reliability at the cost of write performance and endurance, requiring complex tuning of parameters for each device, which is inefficient and reduces initial power-up performance.
Innovation Solution
A method is introduced to determine optimized row-based or wordline-based programming parameters by training on multiple NAND flash memory devices, using a test circuit to precondition blocks and adjust parameters based on result metrics like average programming time and bit-error rate, allowing for common parameter sets to be applied across devices, thereby improving write performance and endurance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional Program DSP methods are used to achieve high reliability by modifying NAND parameters and using smaller voltage steps, then Bit-Error Rate is reduced, but programming speed and write performance deteriorate
Solution Approach 1:
The patent applies different programming parameters to different rows based on their physical characteristics. By determining row-based programming parameters using target physical device parameters of the target row and optimized programming parameters corresponding to the physical device parameters, the system tailors the programming approach to local row characteristics, achieving high reliability without uniformly sacrificing programming speed across all rows.
Solution Approach 2:
The patent dynamically adjusts programming parameters based on physical device parameters. By determining optimized programming parameters corresponding to physical device parameters and applying them row-by-row, the system changes parameters adaptively rather than using fixed traditional parameters, resolving the contradiction between reliability and programming speed.
2Reliability
If traditional Program DSP methods are used with complex tuning of parameters for each device, then reliability is improved, but ease of operation and initial power-up performance deteriorate
Solution Approach 1:
The patent performs preliminary determination of optimized programming parameters corresponding to physical device parameters before actual programming operations. By pre-establishing the relationship between physical device parameters and optimized programming parameters, the system eliminates complex real-time tuning during operation, improving ease of operation while maintaining reliability.
Solution Approach 2:
The system determines programming parameters automatically based on physical device parameters without requiring manual tuning for each device. The controller autonomously selects appropriate parameters by determining target physical device parameters and applying corresponding optimized programming parameters, making the system self-sufficient and easy to operate.
Data Source
AI summary
Various implementations described herein relate to systems and methods for programming data, including determining a target row corresponding to a program command and setting row-based programming parameters for the target row using target physical device parameters of the target row and optimized programming parameters corresponding to the physical device parameters.