SSM P/E Cycle Estimation via Error Parameter Sampling
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Solution Overview
Problem
Solid state storage systems face challenges in determining and verifying the Program/Erase (P/E) cycle value of storage modules, which is crucial for assessing their end-of-life and optimizing performance, due to the limited number of write cycles and potential inaccuracies in tracking these cycles, leading to issues like increased latency and data loss.
Innovation Solution
A testing system and method that includes a controller, memory, and optionally a Field Programmable Gate Array (FPGA) to estimate the P/E cycle value by selecting a sample set of physical addresses, performing erase and write requests, generating a known data pattern, reading the data, determining error parameters, and using an in-memory data structure to calculate and store the P/E cycle value.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the number of program-erase cycles is tracked to maximize storage utilization, then storage management reliability is improved, but the complexity of tracking and verifying cycle counts increases
Solution Approach 1:
The storage module performs self-testing by automatically selecting physical addresses, executing erase and write operations, and calculating P/E cycle values without external intervention. The controller autonomously determines error parameters and queries the in-memory data structure to estimate P/E cycles, eliminating the need for complex external tracking infrastructure.
Solution Approach 2:
The patent replaces mechanical/manual tracking of P/E cycles with an electronic/computational approach. Instead of physically counting and recording write cycles, the system uses error parameter measurements from read operations and queries a pre-populated in-memory data structure to estimate P/E cycle values, substituting direct measurement with indirect computational estimation.
2Reliability
If P/E cycle information is accurately tracked to prevent data loss, then data reliability is improved, but the time and resources required for tracking increase
Solution Approach 1:
The in-memory data structure is pre-populated with relationships between error parameters and P/E cycle values before runtime operations. This preliminary preparation allows the controller to quickly estimate P/E cycles by simply querying the pre-computed data structure, avoiding time-consuming real-time analysis or extensive tracking during storage operations.
Solution Approach 2:
Instead of tracking every single write operation to maintain precise P/E cycle counts, the system performs partial tracking by sampling error parameters from read operations and using these partial measurements to estimate overall P/E cycle values. This partial action approach reduces tracking overhead while maintaining sufficient accuracy for data protection decisions.
3Productivity
If storage module wear is monitored to optimize performance, then performance optimization is improved, but the complexity of monitoring and assessment increases
Solution Approach 1:
The patent extracts only the essential information needed for wear monitoring by measuring specific error parameters from read operations. Instead of monitoring all possible storage characteristics, the system focuses on extracting error parameter data that directly correlates with P/E cycle wear, simplifying the monitoring process while maintaining effectiveness for performance optimization.
Data Source
AI summary
In general, embodiments of the technology relate to a method for characterizing persistent storage. The method includes selecting a sample set of physical addresses in a solid state memory module, where the sample set of physical addresses is associated with a region in the solid state memory module (SSMM). The method further includes issuing a write request to the sample set of physical addresses, after issuing the write request, issuing a request read to the sample set of physical addresses to obtain a copy of the data stored in the sample set of physical addresses, obtaining an error parameter for the copy of the data, determining a calculated P/E cycle value for the SSMM using at least the error parameter; and storing the calculated P/E cycle value in the SSMM.