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公开(公告)号：US12106076B2
公开(公告)日：2024-10-01
申请号：US17853090
申请日：2022-06-29
Applicant: MOREH CORP.
Inventor： Jaejin Lee , Wookeun Jung
Abstract: The present disclosure relates to a method for generating a program for use in an accelerator for deep learning. The method may include receiving, by a computing device, a deep learning application, generating an element-wise operation list included in the deep learning application, generating an intermediate expression from the element-wise operation list, and generating, based on the intermediate expression, a program for use in an accelerator for the deep learning application.
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公开(公告)号：US20220326922A1
公开(公告)日：2022-10-13
申请号：US17853028
申请日：2022-06-29
Applicant: MOREH CORP.
Inventor： Jaejin Lee , Wookeun Jung
Abstract: The present disclosure relates to a method for automatically optimizing a program based on reinforcement learning. The method for automatically optimizing a program based on reinforcement learning includes (a) receiving an input for a source program, which includes a fixed parameter and variable parameter, (b) generating the source program based on the received input, (c) converting the source program into an object program, (d) executing the converted object program to measure a performance of the executed object program, (e) inputting the variable parameter and the measured performance into a machine learning model, and outputting a variation of the variable parameter, and (f) regenerating a source program reflecting the variation of the variable parameter.
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Patent Agency Ranking
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.
Inventor： Jaejin Lee , Jungho Park , Youngdong Do
IPC: G06N3/08
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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公开(公告)号：US12026487B2
公开(公告)日：2024-07-02
申请号：US17853028
申请日：2022-06-29
Applicant: MOREH CORP.
Inventor： Jaejin Lee , Wookeun Jung
Abstract: A method for automatically optimizing a program based on reinforcement learning includes (a) receiving an input for a source program, which includes a fixed parameter and variable parameter, (b) generating the source program based on the received input, (c) converting the source program into an object program, (d) executing the converted object program to measure a performance of the executed object program, (e) inputting the variable parameter and the measured performance into a machine learning model, and outputting a variation of the variable parameter, and (f) regenerating a source program reflecting the variation of the variable parameter.
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5.发明公开公开(公告)号：US20240118878A1
公开(公告)日：2024-04-11
申请号：US18542544
申请日：2023-12-15
Applicant: MOREH CORP. , Seoul National University R&DB Foundation
Inventor： Jaejin Lee , Jungho Park , Gangwon Jo , Heehoon Kim , Jinpyo Kim
Abstract: A method for determining optimization applicability on an intermediate representation from a program is performed by one or more processors, and includes receiving, as a query, a subgraph of the intermediate representation that is a subject of determination of optimization applicability, determining a validity of the query, and if the query is valid, determining optimization applicability on the subgraph, in which the program includes data and a plurality of operations, and the intermediate representation includes a plurality of data nodes, a plurality of operation nodes, and a plurality of edges representing input/output relationships between the plurality of data nodes and the plurality of operation nodes.
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公开(公告)号：US20240118876A1
公开(公告)日：2024-04-11
申请号：US18542563
申请日：2023-12-15
Applicant: MOREH CORP. , Seoul National University R&DB Foundation
Inventor： Jaejin Lee , Jungho Park , Gangwon Jo , Heehoon KIM , Jinpyo KIM
IPC: G06F8/41
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.
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公开(公告)号：US20220326915A1
公开(公告)日：2022-10-13
申请号：US17853090
申请日：2022-06-29
Applicant: MOREH CORP.
Inventor： Jaejin Lee , Wookeun Jung
Abstract: The present disclosure relates to a method for generating a program for use in an accelerator for deep learning. The method may include receiving, by a computing device, a deep learning application, generating an element-wise operation list included in the deep learning application, generating an intermediate expression from the element-wise operation list, and generating, based on the intermediate expression, a program for use in an accelerator for the deep learning application.
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