Samsung Electronics Co., Ltd.

Jungmin Seo

Byeonghui Kim

Kibeen Jung

Seungjun Yang

Yang Seok Ki

Sangoak Woo

Younggeon Yoo

Chanho Yoon

Wonseb Jeong

Beomkyu Shin

Myungjune Jung

Hyeongyu Min

Jooyoung Hwang

Kangho Roh

Kyoung-Gu Woo

Minkyu Kim

Jupyung Lee

Jaewoong Kim

Seungchul Chae

A storage device includes a nonvolatile memory device and a storage controller. The storage controller includes a multi-protocol host interface circuit that receives a first-type request including a first logical address from an external host and transmits/receives data corresponding to the first-type request with the external host by a block unit. Additionally, the multi-protocol host interface circuit receives a second-type request including a first physical address from the external host and transmits/receives data corresponding to the second-type request with the external host by a unit smaller than the block unit. A mapping cache manager manages an address translation table cache, sends an address translation request including the first physical address to the external host, and receives a response including mapping information corresponding to the first physical address from the external host.

Storage device, operation method of storage device, and storage system using the same

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.

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

A storage device is configured to manage a plurality of nonvolatile memories with a plurality of physical streams. An operation method of the storage device includes receiving an input/output request from an external host device, determining a 0-th virtual stream identifier, extracting a 0-th representative value from a 0-th virtual stream feature, extracting a first and second representative values corresponding to first and second physical streams, calculating distance information including first and second similarities between the 0-th virtual stream and each of the first and second physical streams, based on the extracted representative values, assigning one of the plurality of physical streams to the 0-th virtual stream, based on the distance information, and performing an operation corresponding to the input/output request, at the assigned physical stream, and the extracting and the calculating are performed by using machine learning model.

Storage device configured to support multi-streams and operation method thereof

A storage device includes a memory device storing model information of a machine learning model; and a storage controller that controls an operation of the storage device using the machine learning model. The storage controller, upon receiving a get command for extracting the model information from the host device, reads the model information from the memory device in response to the get command and transmits the model information to the host device.

Storage device for storing model information, storage system including the storage device, and operating method of the storage system

A method includes sampling input/output requests from a host to generate sampled input/output requests; classifying the sampled input/output requests into clusters using an unsupervised learning algorithm; determining a hot data range based on a characteristic of the clusters; and incorporating the determined hot data range into a hot data table.

Storage device using unsupervised learning scheme and memory management method thereof

The present disclosure provides an operating method of a storage controller. The operating method includes receiving user data and environmental information, obtaining logical-characteristic information and physical-characteristic information, defining a current state, obtaining expectation values, and performing a write operation. User data and environmental information is received from a non-volatile memory. The current state may be defined based on the logical-characteristic information and the physical-characteristic information. Expectation values may be obtained based on policy information and the current state. The write operation may be performed on the user data through a physical stream corresponding to a maximum value among the expectation values.

Storage controller and storage device including the same and operating method thereof

A storage device is provided. In relation to the storage device operating in an active mode and a low power mode, the storage devices includes a nonvolatile memory including a plurality of nonvolatile memory cells, and a storage controller configured to process commands inputted from a host device in the active mode, wherein the storage controller includes a power mode manager that adjusts the plurality of power modes, wherein, when a first command is inputted, the power mode manager predicts an input prediction time for a second command to be inputted from the host device after the first command, changes from the active mode to the low power mode when a processing operation of the first command is completed, and returns to the active mode from the low power mode when a set return time elapses according to the input prediction time.

Storage device and method of operating the same

A distributed processing system includes a plurality of task nodes each configured to have a capability of processing a task using a reconfigurable processor, and having a capability of processing the task using a non-reconfigurable processor if the task is not processed using the reconfigurable processor, and a scheduler node configured to select a task node that is to process the task from the plurality of task nodes.

Growing community of inventors

Seongnam-si, South Korea

Jungmin Seo