Electronic apparatus and controlling method thereof

Patent metadata

Field	Value
Publication number	US-12412123-B2
Application number	US-202117528605-A
Country	US
Kind code	B2
Filing date	Nov 17, 2021
Priority date	Nov 20, 2020
Publication date	Sep 9, 2025
Grant date	Sep 9, 2025

Abstract

An electronic device may include a communicator and a processor configured to, based on characteristic information of a dataset for performing a job included in a queue, identify a type of a preloader configured to preload the dataset, and control the communicator to transmit the preloader of the identified type to at least one computing device among a plurality of computing devices. The job may be related to performing training of an AI model by using the dataset. The preloader of a first type may copy the dataset stored in at least one external storage device and store the dataset in the at least one computing device, and the preloader of a second type may generate a connecting link for the dataset stored in the at least one external storage and store the connecting link in the at least one computing device.

First claim

What is claimed is:

1. An electronic apparatus comprising:
a communication interface; and
a processor configured to:
based on characteristic information of a dataset to be used to perform a job included in a queue, identify a type of a preloader configured to preload the dataset; and
control the communication interface to transmit the preloader of the identified type to at least one computing device among a plurality of computing devices,

wherein the preloader includes a preloader of a first type and a preloader of a second type,
wherein the preloader of the first type is configured to copy the dataset stored in at least one external storage device and store the dataset in the at least one computing device,
wherein the preloader of the second type is configured to generate a connecting link for the dataset stored in the at least one external storage device and store the connecting link in the at least one computing device,
wherein the job relates to performing training of an artificial intelligence (AI) model by using the at least one computing device based on the dataset,
wherein the characteristic information of the dataset includes at least one of a size of the dataset or a number of files of the dataset, and
wherein the processor is further configured to:
based on the number of files included in the dataset being greater than or equal to a predetermined number, control the communication interface to transmit the preloader of the first type to the at least one computing device,
based on the number of files included in the dataset being smaller than the predetermined number, control the communication interface to transmit the preloader of the second type to the at least one computing device,
based on the size of the dataset being smaller than a predetermined size, control the communication interface to transmit the preloader of the first type to the at least one computing device, and
based on the size of the dataset being greater than or equal to the predetermined size, control the communication interface to transmit the preloader of the second type to the at least one computing device.

2. The electronic apparatus of claim 1 , wherein the processor is further configured to:
based on preloading information received from the plurality of computing devices through the communication interface, identify at least one computing device in which the dataset is preloaded among the plurality of computing devices.

3. The electronic apparatus of claim 2 , wherein the processor is further configured to:
based on identifying the at least one computing device in which the dataset is preloaded, control the communication interface to transmit a command for performing the job to the identified at least one computing device.

4. The electronic apparatus of claim 2 , wherein the processor is further configured to:
based on identifying that there is no computing device in which the dataset is preloaded, adjust the job to be a last order in the queue.

5. The electronic apparatus of claim 2 , wherein the processor is further configured to:
based on a number of jobs for which the dataset is required in the queue being greater than a number of a computing device in which the dataset is preloaded, control the communication interface to transmit the preloader of the identified type to at least one computing device among remaining computing devices of the plurality of computing devices, excluding the computing device in which the dataset is preloaded.

6. The electronic apparatus of claim 2 , wherein the processor is further configured to:
based on a number of jobs for which the dataset is required in the queue being smaller than a number of computing devices in which the dataset is preloaded, control the communication interface to transmit a command for deleting the preloader of the identified type to at least one computing device among the computing devices in which the dataset is preloaded.

7. The electronic apparatus of claim 1 , wherein the processor is further configured to:
based on receiving a user command requesting training of the AI model by using the dataset, arrange the job in the queue.

8. A method of controlling an electronic apparatus, the method comprising:
based on characteristic information of a dataset to be used to perform a job included in a queue, identifying a type of a preloader configured to preload the dataset; and
transmitting the preloader of the identified type to at least one computing device among a plurality of computing devices,
wherein the preloader includes a preloader of a first type and a preloader of a second type,
wherein the preloader of the first type is configured to copy the dataset stored in at least one external storage device and store the dataset in the at least one computing device,
wherein the preloader of the second type is configured to generate a connecting link for the dataset stored in the at least one external storage device and store the connecting link in the at least one computing device,
wherein the job is related to performing training of an artificial intelligence (AI) model by using the at least one computing device based on the dataset,
wherein the characteristic information of the dataset includes at least one of a size of the dataset or a number of files of the dataset, and
wherein the transmitting comprises:
based on the number of files included in the dataset being greater than or equal to a predetermined number, transmitting the preloader of the first type to the at least one computing device,
based on the number of files included in the dataset being smaller than the predetermined number, transmitting the preloader of the second type to the at least one computing device,
based on the size of the dataset being smaller than a predetermined size, transmitting the preloader of the first type to the at least one computing device, and
based on the size of the dataset being greater than or equal to the predetermined size, transmitting the preloader of the second type to the at least one computing device.

9. The method of claim 8 , further comprising:
based on preloading information received from the plurality of computing devices, identifying at least one computing device in which the dataset is preloaded among the plurality of computing devices.

Assignees

• Samsung Electronics Co Ltd

Inventors

• Park Eunsoo

Classifications

• G06F2209/506

  Constraint · CPC title

• G06F9/4881

  Scheduling strategies for dispatcher, e.g. round robin, multi-level priority queues · CPC title

• G06F2209/501

  Performance criteria · CPC title

• G06F9/546

  Message passing systems or structures, e.g. queues · CPC title

• G06F9/5011

  the resources being hardware resources other than CPUs, Servers and Terminals · CPC title