Apparatus and computer-implemented method for determining a memory plan for executing operations

US2025378317A1 · US · A1

Patent metadata
FieldValue
Publication numberUS-2025378317-A1
Application numberUS-202519209298-A
CountryUS
Kind codeA1
Filing dateMay 15, 2025
Priority dateMay 24, 2024
Publication dateDec 11, 2025
Grant date

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  1. Title

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  2. Abstract

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  4. Key dates

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  5. First independent claim

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  6. CPC / IPC classifications

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Abstract

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An apparatus and computer-implemented method for determining a memory plan for executing operations, in particular of an artificial neural network. A list of memory areas required for executing the operations is created, wherein, depending on the list, it is determined for the operations which memory areas must be present in a first memory for executing the particular operation and which memory areas may be present in a second memory during the execution of the particular operation, wherein the memory plan is determined depending on whether a memory area must be present in the main memory for execution or may be present in the secondary memory.

First claim

Opening claim text (preview).

1 - 5 . (canceled) 6 . A computer-implemented method for determining a memory plan for executing operations of an artificial neural network, the method comprising the following steps: creating a list of memory areas required for executing the operations; depending on the list, determining for the operations which memory areas must be present in a first memory for executing a respective operation and which memory areas may be present in a second memory during the execution of the respective operation; determining the memory plan depending on whether a memory area must be present in the first memory for execution or may be present in the second memory; for each operation, determining an assignment of the memory areas one of the the first memory and to the second memory; for each operation, marking the memory areas in the list that do not have to be in the first memory are marked; and determining the memory plan depending on the list with the marked memory areas, and determining the assignment that minimizes a number of transfers of memory areas between the first memory and the second memory. 7 . The method according to claim 6 , wherein the assignment is determined using a satisfiability modulo theories solver. 8 . The method according to claim 6 , wherein the memory areas for executing the operations are provided according to the memory plan, wherein certain of the memory areas are transferred from the first memory to the second memory or are transferred from the second memory to the first memory according to the memory plan. 9 . An apparatus for determining a memory plan for executing operations of an artificial neural network, the apparatus comprising: at least one processor; and at least one memory, wherein the at least one memory includes instructions which can be executed by the at least one processor, and, upon execution of which by the at least one processor, the following steps are executed: creating a list of memory areas required for executing the operations, depending on the list, determining for the operations which memory areas must be present in a first memory for executing a respective operation and which memory areas may be present in a second memory during the execution of the respective operation, determining the memory plan depending on whether a memory area must be present in the first memory for execution or may be present in the second memory, for each operation, determining an assignment of the memory areas one of the the first memory and to the second memory, for each operation, marking the memory areas in the list that do not have to be in the first memory are marked, and determining the memory plan depending on the list with the marked memory areas, and determining the assignment that minimizes a number of transfers of memory areas between the first memory and the second memory. 10 . A non-transitory storage medium on which is stored a computer program including computer-readable instructions for determining a memory plan for executing operations of an artificial neural network, the instructions, when executed by at least one processor, causing the at least one comprising the following steps: creating a list of memory areas required for executing the operations; depending on the list, determining for the operations which memory areas must be present in a first memory for executing a respective operation and which memory areas may be present in a second memory during the execution of the respective operation; determining the memory plan depending on whether a memory area must be present in the first memory for execution or may be present in the second memory; for each operation, determining an assignment of the memory areas one of the the first memory and to the second memory; for each operation, marking the memory areas in the list that do not have to be in the first memory are marked; and determining the memory plan depending on the list with the marked memory areas, and determining the assignment that minimizes a number of transfers of memory areas between the first memory and the second memory.

Assignees

Inventors

Classifications

  • G06N3/063Primary

    using electronic means · CPC title

  • Improving the reliability of storage systems · CPC title

  • G06F3/0604Primary

    Improving or facilitating administration, e.g. storage management · CPC title

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What does patent US2025378317A1 cover?
An apparatus and computer-implemented method for determining a memory plan for executing operations, in particular of an artificial neural network. A list of memory areas required for executing the operations is created, wherein, depending on the list, it is determined for the operations which memory areas must be present in a first memory for executing the particular operation and which memory…
Who is the assignee on this patent?
Bosch Gmbh Robert
What technology area does this patent fall under?
Primary CPC classification G06N3/063. Mapped technology areas include Physics.
When was this patent published?
Publication date Thu Dec 11 2025 00:00:00 GMT+0000 (Coordinated Universal Time) (A1). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 8 related publications on this page (citations in our corpus or others sharing the same primary CPC).