Storage Device LBA Predictor Neural Network Write Amplification

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Solution Overview

Problem

Storage devices with nonvolatile memory face write amplification issues due to skewed ratios of write operations, leading to reduced performance and increased wear on memory cells, especially when performing randomly addressed write operations without accurate Logical Block Address (LBA) assignment.

Innovation Solution

A storage device equipped with a buffer memory and an LBA predictor using a neural network model to accurately predict LBA values for data lacking stream IDs, thereby assigning appropriate stream IDs and reducing unnecessary write operations, which mitigates write amplification by optimizing LBA assignments.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If the storage device performs randomly addressed write operations without accurate LBA assignment, then the device can handle diverse write operations, but write amplification increases and performance decreases

Engineering Contradiction:

Improveability to handle diverse write operationsVSAvoidwrite performance

Core Design Contradiction:

Adaptability or versatilityVSProductivity

Solution Approach 1:

The neural network model performs preliminary prediction of LBA values before actual write operations occur. By predicting the LBA values in advance based on historical data patterns, the system can pre-assign stream IDs and optimize the write operation sequence, thereby improving write performance while maintaining adaptability to diverse write operations.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements feedback mechanisms by continuously monitoring and learning from actual write operation patterns. The neural network model uses historical LBA assignment data as feedback to refine its predictions, creating a closed-loop system that adapts to changing write patterns and optimizes performance over time.

Inventive Principle:

Principle #23Feedback

2Adaptability or versatility

If the storage device performs randomly addressed write operations, then the device can accommodate various data streams, but the wear of nonvolatile memory cells increases

Engineering Contradiction:

Improveability to accommodate various data streamsVSAvoiddurability of nonvolatile memory cells

Core Design Contradiction:

Adaptability or versatilityVSReliability

Solution Approach 1:

By predicting LBA values in advance and pre-assigning stream IDs, the system avoids random write patterns that cause uneven wear. The preliminary action of optimizing LBA assignment based on historical data ensures that subsequent write operations follow a more uniform pattern, reducing peak wear on specific memory cells while maintaining the ability to accommodate various data streams.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system changes the parameter of LBA assignment strategy from random to predicted/optimal based on historical patterns. By transforming the assignment approach using neural network predictions, the system achieves more uniform write distribution across memory cells, thereby reducing wear and improving reliability while preserving adaptability.

Inventive Principle:

Principle #35Parameter changes

3Device complexity

If the storage device uses traditional LBA assignment methods, then the device structure remains simple, but write amplification occurs and performance degrades

Engineering Contradiction:

Improvesimplicity of LBA assignment structureVSAvoidwrite performance

Core Design Contradiction:

Device complexityVSProductivity

Solution Approach 1:

The patent replaces traditional mechanical/LBA-based assignment mechanisms with a neural network-based prediction system. This substitution uses machine learning models to predict optimal LBA values and assign stream IDs, transforming the assignment process from simple rule-based mechanisms to intelligent prediction-driven systems, thereby improving performance while managing complexity through automation.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS11429314B2Storage device, storage system and operating method thereof

Publication Date: 2022.08.30 SAMSUNG ELECTRONICS CO LTD

AI summary

A storage device includes; an interface receiving data and a corresponding LBA from a host, wherein the data includes at least one of first data having a stream ID and second data lacking a stream ID, a nonvolatile memory (NVM) device including at least one nonvolatile memory configured to store the data, and a LBA predictor configured to provide a predicted stream ID for the second data using a neural network model operating in response to at least one feature associated with LBA values received by the storage device from the host, wherein the first data is stored in the NVM device using the stream ID, and the data is stored in the NVM device using the predicted stream ID.