ECC Decode Scheduling for Autonomous Multi-Phase Error Correction
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Solution Overview
Problem
The complexity of designing and implementing multi-phase error correction coding (ECC) decoders in non-volatile data storage devices increases due to the need for multiple decoding phases and the generation of redundant information, making it challenging to correct errors effectively.
Innovation Solution
A schedule-based ECC decode controller populates a decoding schedule for data chunks, initiating decoding in a pipelined operation with stages for fetching, decoding, and writing back, using a stack or stack-on-stack configuration to manage data chunks and parity bits, allowing for reduced complexity and self-sustained operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multi-phase ECC decoding is implemented to increase error correction capacity, then error correction capability is improved, but device complexity increases
Solution Approach 1:
The ECC decoding process is segmented into multiple phases: a first phase using a reduced set of parity bits for initial decoding attempts, and a second phase using a larger set of parity bits for more powerful decoding when the first phase fails. This segmentation allows the system to achieve high error correction capability while managing complexity by breaking down the decoding task into manageable stages.
Solution Approach 2:
The system performs preliminary decoding using a reduced set of parity bits before attempting full decoding with the complete parity bit set. This preliminary action filters out many decoding cases that can be resolved with minimal resources, reserving the more complex full decoding process only for cases that truly require it, thereby reducing overall operational complexity.
2Reliability
If a larger set of parity bits is used for powerful decoding, then error correction capacity increases, but the number of bits required to store encoded data increases
Solution Approach 1:
The parity bits are segmented into a reduced set and a larger set. The reduced set is used for initial decoding attempts on individual chunks, while the larger set is reserved for secondary decoding when needed. This segmentation allows the system to maintain high error correction capacity while reducing the average number of bits stored and processed for each chunk.
Solution Approach 2:
The system applies partial decoding using only the reduced set of parity bits for most chunks, and applies the full larger set of parity bits only when necessary (excessive action). This approach ensures that the majority of decoding operations use fewer bits, while maintaining the capability to handle difficult error cases with the complete parity bit set.
3Reliability
If multi-phase ECC decoding is implemented, then error correction capability is improved, but implementation complexity and debugging difficulty increase
Solution Approach 1:
The ECC decode controller autonomously manages the multi-phase decoding process by automatically determining when to transition from the first phase to the second phase based on decoding success or failure. This self-service approach eliminates the need for complex external control logic and simplifies implementation, as the controller independently handles the complexity of phase management and debugging.
Solution Approach 2:
The system uses feedback from the first phase decoding results to control the transition to the second phase. When decoding fails in the first phase, the system automatically triggers the second phase with the larger parity bit set. This feedback mechanism simplifies implementation by providing clear, automated decision-making logic rather than requiring complex external control.
Data Source
AI summary
A method includes receiving, at an error correction coding (ECC) controller, information indicating one or more data chunks to be decoded, populating a schedule according to an order of decoding of the data chunks, and initiating decode of the data chunks according to the schedule.