NAND Flash LDPC Decoding With Syndrome-Weight Early Exit
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Solution Overview
Problem
Current error correction systems in NAND flash storage, particularly LDPC codes, face challenges in latency and processing performance due to iterative decoding processes that consume time and resources, often failing to meet latency and processing requirements in latency-sensitive applications.
Innovation Solution
A data processing system with a controller that includes multiple decoders, allowing for fast decoding with shorter latency when certain conditions are met, and a method for predicting page health by monitoring syndrome weight and iteration number to terminate LDPC decoding early, reducing unnecessary iterations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If iterative decoding process is used for LDPC codes, then error correction performance is improved, but decoding latency and processing time increase
Solution Approach 1:
The patent implements early termination of the iterative decoding process by monitoring the syndrome weight after each iteration. When the syndrome weight becomes zero (indicating successful error correction) or exceeds a threshold (indicating uncorrectable errors), the decoding process is terminated immediately, skipping unnecessary remaining iterations. This reduces decoding latency while maintaining error correction performance by avoiding redundant processing steps.
Solution Approach 2:
The patent introduces a feedback mechanism where the syndrome weight is calculated and monitored after each decoding iteration. This feedback information is used to dynamically control the continuation or termination of the decoding process. The controller adjusts the number of iterations based on the syndrome weight feedback, optimizing the balance between error correction performance and decoding speed.
2Reliability
If maximum number of iterations is performed, then error correction capability is maximized, but processing burden and power consumption increase
Solution Approach 1:
The patent applies partial action by performing only the necessary number of decoding iterations required to achieve error correction, rather than always executing the maximum number of iterations. The iteration count is dynamically adjusted based on syndrome weight monitoring, performing fewer iterations when errors are corrected early and avoiding unnecessary processing steps, thereby improving processing efficiency while maintaining adequate error correction capability.
3Speed
If syndrome weight monitoring is implemented for early termination, then decoding speed is improved, but system complexity increases
Solution Approach 1:
The patent implements a self-service mechanism where the decoding process automatically monitors its own syndrome weight and makes termination decisions based on predefined thresholds. The syndrome weight calculation and comparison logic are integrated into the decoding process itself, allowing the system to autonomously determine when to terminate without requiring complex external control mechanisms, thus improving decoding speed with minimal additional complexity.
Data Source
AI summary
A data processing system includes a storage medium, and a controller including a data processing block, configured to receive data from a host, transmit the received data to the storage medium, read data from the storage medium in response to a read request from the host, and decode the read data by the data processing block according to multiple decoding modes. The data processing block includes a first decoder and a second decoder, and is configured to manage the first decoder and the second decoder to run the decoding for the read data, and activate a fast decoding having shorter latency than a normal decoding after a fast decoding condition is satisfied.