Samsung electronics co., ltd. (20240176743). STORAGE DEVICE PREDICTING ACCESS AND REPRODUCING DATA simplified abstract
Contents
- 1 STORAGE DEVICE PREDICTING ACCESS AND REPRODUCING DATA
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 STORAGE DEVICE PREDICTING ACCESS AND REPRODUCING DATA - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
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 20240176743 titled 'STORAGE DEVICE PREDICTING ACCESS AND REPRODUCING DATA
Simplified Explanation
The storage device described in the patent application utilizes machine learning to predict and prefetch data based on repeated logical address patterns requested by a host. Here are some key points to explain the innovation:
- The storage controller detects repeated logical address patterns requested by a host.
- It divides the logical address pattern into input logical addresses and predictive logical addresses.
- A reproduction model is generated using machine learning to generate reproduction data for the predictive logical addresses.
- When a read request is received for the input logical addresses, the storage controller predicts the predictive logical addresses, generates reproduction data, and prefetches it to a buffer memory.
Potential Applications
This technology can be applied in various storage devices such as solid-state drives (SSDs) and hard disk drives (HDDs) to improve data access speeds and efficiency.
Problems Solved
1. Addressing data access latency by predicting and prefetching data based on repeated patterns. 2. Enhancing overall storage device performance by utilizing machine learning for data reproduction.
Benefits
1. Faster data access speeds for frequently requested data. 2. Improved overall storage device efficiency and performance. 3. Reduced latency in data retrieval processes.
Potential Commercial Applications
"Predictive Data Prefetching Technology for Storage Devices" can be utilized in enterprise storage solutions, cloud storage services, and consumer electronics to enhance data access speeds and optimize storage performance.
Possible Prior Art
One possible prior art in this field is the use of caching algorithms in storage devices to improve data access speeds and reduce latency. However, the use of machine learning for predictive data prefetching as described in this patent application is a novel approach to further enhance storage device performance.
Unanswered Questions
How does this technology impact power consumption in storage devices?
The patent application does not provide information on the potential impact of this technology on power consumption in storage devices. It would be interesting to know if predictive data prefetching affects power efficiency.
Can this technology be applied to different types of nonvolatile memory devices?
The patent application focuses on utilizing machine learning for predictive data prefetching in a storage device. It would be beneficial to explore if this technology can be implemented in various types of nonvolatile memory devices such as NAND flash memory or 3D XPoint technology.
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.
