公开(公告)号：US20210200477A1

公开(公告)日：2021-07-01

申请号：US17136818

申请日：2020-12-29

Applicant: Samsung Electronics Co., Ltd.

Inventor： Jungmin SEO ,  Byeonghui KIM ,  Kibeen JUNG ,  Seungjun YANG

IPC: G06F3/06 ,  G06N20/00

Abstract: 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.

公开(公告)号：US20250094051A1

公开(公告)日：2025-03-20

申请号：US18592065

申请日：2024-02-29

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： Byeonghui KIM ,  Seongho Roh ,  Hyeongyu Min ,  Jisoo Kim ,  Hyunkyo Oh ,  Han Kyoo Lee ,  Kibeen Jung

IPC: G06F3/06

Abstract: A storage device includes: at least one nonvolatile memory device configured to store or read data; and at least one controller configured to: control the at least one nonvolatile memory device, perform at least one workload of a plurality of workloads, based on at least one parameter, perform a tuning for improvement of a performance and a Quality-of-Service (QOS) conformity with a first storage device associated with the workload, and wherein the at least one controller is further configured to individually perform the tuning for each of the plurality of workloads that are different kinds.

公开(公告)号：US20210200454A1

公开(公告)日：2021-07-01

申请号：US17038371

申请日：2020-09-30

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： Byeonghui KIM ,  Jungmin SEO ,  Kangho ROH ,  Hyeongyu MIN ,  Jooyoung HWANG

IPC: G06F3/06 ,  G06N20/00

Abstract: 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.

公开(公告)号：US20250045104A1

公开(公告)日：2025-02-06

申请号：US18409286

申请日：2024-01-10

Applicant: Samsung Electronics Co., Ltd.

Inventor： Kibeen JUNG ,  Minkyu KIM ,  Hankyoo LEE ,  Namhoon KIM ,  Byeonghui KIM ,  Jisoo KIM ,  Hyunkyo OH

IPC: G06F9/50 ,  G06F1/324

Abstract: A storage device includes at least one nonvolatile memory device, and a controller controlling the at least one nonvolatile memory device. The controller includes a parameter storage storing a power parameter indicating a clock value of each of internal configurations for each power state. The power parameter is a value derived by performing machine learning considering performance, peak power, and average power.

公开(公告)号：US20240168674A1

公开(公告)日：2024-05-23

申请号：US18127922

申请日：2023-03-29

Applicant: Samsung Electronics Co., Ltd.

Inventor： Kibeen JUNG ,  Han Kyoo LEE ,  Byeonghui KIM ,  Hyunkyo OH ,  Sungmin JANG

IPC: G06F3/06

CPC classification number: G06F3/0653 ,  G06F3/061 ,  G06F3/0656 ,  G06F3/0679

Abstract: A throttling method for a storage device is provided. The throttling method includes: receiving a write command from a host; identifying, using a first machine learning model, a throttling delay time; transmitting a completion message to the host according to the throttling delay time; collecting weights of the first machine learning model and performance information of the storage device corresponding to the weights; learning the weights and the performance information to generate an objective function indicating a relationship between the weights and the performance information using a second machine learning model of a weight learning device; selecting a weight corresponding to a maximum performance using the objective function; and updating the first machine learning model with the weight.