Methods and System for Performing Checkpointing Forfault Tolerance in Application

    公开(公告)号:US20240303161A1

    公开(公告)日:2024-09-12

    申请号:US18592791

    申请日:2024-03-01

    Applicant: MOREH CORP.

    CPC classification number: G06F11/1407 G06F11/1461

    Abstract: A method for performing checkpointing for fault tolerance of an application is provided, which is performed by one or more processors, and includes storing accelerator data associated with an application at a specific time point as a checkpoint, storing operation data associated with the application performed after the specific time point, and performing application fault tolerance based on the checkpoint and the stored operation data.

    METHOD AND APPARATUS FOR PIPELINE PARALLELISM COMPILING

    公开(公告)号:US20240303057A1

    公开(公告)日:2024-09-12

    申请号:US18427074

    申请日:2024-01-30

    Applicant: MOREH CORP.

    CPC classification number: G06F8/456

    Abstract: A method for pipeline parallelism compiling is provided, which is executed by one or more processors, and includes receiving a source program associated with training of a machine learning model, determining, based on the source program, a plurality of operation groups including operations executed on training data of the machine learning model, generating a plurality of micro-batches from the training data, and determining, for each of the plurality of micro-batches, a plurality of operation sets corresponding to the plurality of operation groups.

    METHOD AND SYSTEM FOR PARALLELLY PROCESSING CALL LIST ASSOCIATED WITH ARTIFICIAL INTELLIGENCE CALCULATION

    公开(公告)号:US20240303138A1

    公开(公告)日:2024-09-12

    申请号:US18422655

    申请日:2024-01-25

    Applicant: MOREH CORP

    CPC classification number: G06F9/542

    Abstract: Provided is a method for parallelly processing a call list associated with an artificial intelligence calculation performed by one or more processors, including acquiring an original call list including a plurality of primitive operations, determining a number of accelerators to parallelly process the original call list, creating a plurality of sub call lists based on the determined number of accelerators and the original call list, and transmitting each of the created plurality of sub call lists to each of a plurality of accelerators corresponding to the determined number.

    METHOD AND SYSTEM FOR MANAGING INTERMEDIATE REPRESENTATION FROM PROGRAM

    公开(公告)号:US20240118876A1

    公开(公告)日:2024-04-11

    申请号:US18542563

    申请日:2023-12-15

    CPC classification number: G06F8/41

    Abstract: A method for managing an intermediate representation from a program is executed by one or more processors, and includes extracting, from the program, information on data for input and output and information on operation, generating an intermediate representation from the program using the extracted information on data and the extracted information on operation, storing, in a database, a corresponding relationship between the program and the intermediate representation, storing execution information on operation of the intermediate representation, and deleting at least a part of the intermediate representation based on the execution information.

    METHOD AND SYSTEM FOR COMPILING APPLICATIONS

    公开(公告)号:US20240303056A1

    公开(公告)日:2024-09-12

    申请号:US18595911

    申请日:2024-03-05

    Applicant: MOREH CORP.

    CPC classification number: G06F8/4441

    Abstract: A method for compiling an application is executed by one or more processors, and includes acquiring profiling information of a system on which an application is to be executed, generating a cost model based on the profiling information, acquiring an intermediate representation of at least a portion of the application, applying compiler passes to the intermediate representation and generating a compiled graph, and using the cost model, determining an expected execution time for the compiled graph.

    Method And System for Compiling Applications

    公开(公告)号:US20240303053A1

    公开(公告)日:2024-09-12

    申请号:US18595822

    申请日:2024-03-05

    Applicant: MOREH CORP

    CPC classification number: G06F8/443

    Abstract: The disclosure relates to a method for compiling an application, in which the method is executed by one or more processors, and includes initiating generating a first intermediate representation for a first part of an application, while generating the first intermediate representation, stopping generating the first intermediate representation if it is determined that a number of operation nodes included in the first intermediate representation reaches an interval value, and compiling the generated first intermediate representation.

    METHOD AND SYSTEM FOR COMPILING APPLICATIONS

    公开(公告)号:US20240303051A1

    公开(公告)日:2024-09-12

    申请号:US18595962

    申请日:2024-03-05

    Applicant: Moreh Corp.

    CPC classification number: G06F8/41

    Abstract: A method for compiling an application is executed by one or more processors, and includes acquiring profiling information of a system on which an application is to be executed, generating a cost model based on the profiling information, acquiring an intermediate representation of at least a portion of the application, applying compiler passes to the intermediate representation and generating a compiled graph, and using the cost model, determining an expected execution time for the compiled graph.

    METHOD FOR PROCESSING DEEP LEARNING TASK IN HETEROGENEOUS ACCELERATORS AND CLUSTER SYSTEM FOR PERFORMING THE METHOD

    公开(公告)号:US20230031226A1

    公开(公告)日:2023-02-02

    申请号:US17964626

    申请日:2022-10-12

    Applicant: MOREH CORP.

    Abstract: Provided is a method for processing a deep learning task through a deep learning framework. The method may include executing, by a computing device, a deep learning task on a deep learning framework, determining at least one of a primary accelerator or a secondary accelerator to execute the deep learning task, allocating the deep learning task to at least one of the determined primary accelerator or secondary accelerator, and generating, based on a result processed by at least one of the determined primary accelerator or secondary accelerator, result data for the deep learning task. The secondary accelerator may be an accelerator heterogeneous to the primary accelerator.

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