Storage Controller On-Chip Valley Search Distribution Type
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Solution Overview
Problem
Existing storage systems face challenges in determining the threshold voltage distribution type of non-volatile memory devices, leading to inefficiencies in data retrieval and storage reliability due to the lack of effective methods for obtaining distribution information without increasing I/O load and latency.
Innovation Solution
A storage controller is developed that performs an on-chip valley search (OVS) to generate and analyze OVS count data, determining the distribution type of memory regions and adjusting subsequent operations based on this analysis, thereby improving data retrieval reliability and reducing additional read requests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional methods are used to determine threshold voltage distribution type, then measurement precision is insufficient, but implementing new measurement methods increases I/O load and latency
Solution Approach 1:
The patent performs on-chip valley search (OVS) during the programming process itself, before normal read operations are needed. By determining the distribution type as part of the programming sequence rather than as a separate measurement step, the system obtains accurate distribution information without adding I/O latency to the normal read path.
Solution Approach 2:
The memory device performs the valley search and distribution type determination internally using its own resources during programming. The device generates OVS count data by comparing programmed values against reference valleys without requiring external measurement equipment or additional I/O operations, making the measurement process self-contained and eliminating external I/O overhead.
2Measurement precision
If additional read requests are sent to obtain distribution information, then measurement precision improves, but I/O load increases
Solution Approach 1:
The patent combines the distribution measurement function with the existing programming operation. The OVS process is merged into the programming sequence, where the same programming pulses and data paths are used for both programming and distribution characterization. This consolidation eliminates the need for separate read requests dedicated to measurement, maintaining I/O throughput while obtaining accurate distribution information.
Solution Approach 2:
The programming operation is designed to serve multiple functions simultaneously: it programs the data, performs the on-chip valley search, and generates distribution type information. By making the programming process multi-functional, the system eliminates the need for dedicated measurement operations, thereby maintaining high I/O productivity while achieving precise distribution characterization.
3Measurement precision
If conventional read operations are used for distribution measurement, then device complexity remains low, but measurement precision is insufficient
Solution Approach 1:
The patent modifies the programming operation parameters to enable distribution measurement. By changing the programming sequence to include OVS-specific pulses and comparison operations, the system transforms a simple programming function into a multi-functional operation that also performs distribution characterization. This parameter modification approach avoids adding complex dedicated measurement hardware while achieving high measurement precision.
Data Source
AI summary
Disclosed is a method of operating a storage controller which communicates with a non-volatile memory device. The method includes outputting a first command including a request for on-chip valley search (OVS) count data of a memory region of the non-volatile memory device to the non-volatile memory device, wherein the OVS count data includes a first count value and a second count value of a first read voltage and a third count value and a fourth count value of a second read voltage, receiving the OVS count data from the non-volatile memory device, determining a distribution type of the memory region to be a predicted distribution type, from among a plurality of distribution types, based on the OVS count data, and determining a subsequent operation, based on the predicted distribution type.