Storage controller, storage device, and operation method of storage device

Pending Publication Date: 2022-04-14
SAMSUNG ELECTRONICS CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

[0005]At least one embodiments of the present disclosure provides a storage controller with increased performance and increased

Problems solved by technology

In volatile memory, stored data is lost when a power is turned off.
However, operations of the SSD to generate the data are not o

Method used

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Examples

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Example

[0027]Below, embodiments of the present disclosure are described in detail and clearly to such an extent that one of ordinary skill in the art may implement the present disclosure.

[0028]Components described in the specification by using the terms “part”, “unit”, “module”, “engine”, “manager”, etc. and function blocks illustrated in drawings may be implemented with software, hardware, or a combination thereof. For example, the software may be a machine code, firmware, an embedded code, and application software. For example, the hardware may include an electrical circuit, an electronic circuit, a processor, a computer, an integrated circuit, integrated circuit cores, a pressure sensor, an inertial sensor, a microelectromechanical system (MEMS), a passive element, or a combination thereof.

[0029]FIG. 1 is a block diagram illustrating a storage system according to an exemplary embodiment of the present disclosure. Referring to FIG. 1, a storage system 10 include a host 11 (e.g., a host devi

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PUM

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Abstract

An operation method of a storage device includes receiving a first write request; adding the first write request to a first fragment; selecting at least “n” (e.g., at least two) streams among a plurality of pre-allocated streams when a size of the first fragment, when a size of the first fragment is >=a reference value, based on a cosine similarity between the first fragment and each of the pre-allocated streams; applying input information to a machine learning model to detect a first sequential stream associated with the first fragment from among the at least “n” streams; allocating a stream identifier of the first sequential stream to the first fragment; and storing write data included in the first fragment based on the stream identifier of the first sequential stream. The input information includes statistical information of at least one of the “n” streams and the first fragment.

Description

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Claims

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Application Information

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Owner SAMSUNG ELECTRONICS CO LTD
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