18367584. STORAGE DEVICE PREDICTING ACCESS AND REPRODUCING DATA simplified abstract (Samsung Electronics Co., Ltd.)
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STORAGE DEVICE PREDICTING ACCESS AND REPRODUCING DATA
Organization Name
Inventor(s)
STORAGE DEVICE PREDICTING ACCESS AND REPRODUCING DATA - A simplified explanation of the abstract
This abstract first appeared for US patent application 18367584 titled 'STORAGE DEVICE PREDICTING ACCESS AND REPRODUCING DATA
Simplified Explanation
The storage device described in the abstract is designed to efficiently handle repeated requests for a specific logical address pattern from a host. Here are some key points to explain the innovation:
- The storage controller detects a repeated logical address pattern requested by a host.
- It divides the pattern into input logical addresses and predictive logical addresses.
- A reproduction model is generated using machine learning to predict data corresponding to the predictive logical addresses.
- When a read request is received for the input logical addresses, the controller predicts the predictive logical addresses, generates reproduction data using the reproduction model, and prefetches the data to a buffer memory.
Potential Applications: - Data storage systems - Cloud computing infrastructure - High-performance computing environments
Problems Solved: - Efficient handling of repeated data access patterns - Improved data retrieval speed - Reduction of latency in data access
Benefits: - Enhanced performance in data-intensive applications - Optimized data storage and retrieval processes - Increased overall system efficiency
Potential Commercial Applications:
- Optimizing Data Storage and Retrieval in High-Performance Computing Environments ###
Possible Prior Art: There may be prior art related to predictive data prefetching techniques in storage devices or machine learning-based data prediction models.
Unanswered Questions:
- How does the storage controller handle changes in the logical address pattern over time?
Answer: The storage controller may need to adapt its predictive model based on new patterns observed in the host's data access behavior.
- What impact does the use of machine learning have on the overall performance and resource utilization of the storage device?
Answer: The use of machine learning for predictive data generation may require additional computational resources, which could affect the device's overall efficiency and power consumption.
Original Abstract Submitted
A storage device comprising a nonvolatile memory device, and a storage controller configured to control the nonvolatile memory device wherein the storage controller is configured to, detect a logical address pattern repeatedly requested by a host, divide the logical address pattern into input logical addresses and predictive logical addresses, and generate a reproduction model for generating reproduction data corresponding to the predictive logical addresses in the data pattern when the predictive logical addresses are input using machine learning, and in response to a read request for the input logical addresses from the host, predict the predictive logical addresses using the input logical addresses, generate the reproduction data by inputting the predictive logical addresses into the reproduction model, and prefetch the generated reproduction data to a buffer memory included in the storage controller.
