Distributed Computing based on Memory as a Service

    公开(公告)号:US20230004502A1

    公开(公告)日:2023-01-05

    申请号:US17943739

    申请日:2022-09-13

    Abstract: Systems, methods and apparatuses of distributed computing based on memory as a service are described. For example, a set of networked computing devices can each be configured to execute an application that accesses memory using a virtual memory address region. Each respective device can map the virtual memory address region to the local memory for a first period of time during which the application is being executed in the respective device, map the virtual memory address region to a local memory of a remote device in the group for a second period of time after starting the application in the respective device and before terminating the application in the respective device, and request the remote device to process data in the virtual memory address region during at least the second period of time.

    FEATURE DICTIONARY FOR BANDWIDTH ENHANCEMENT

    公开(公告)号:US20220309291A1

    公开(公告)日:2022-09-29

    申请号:US17841448

    申请日:2022-06-15

    Abstract: A system having multiple devices that can host different versions of an artificial neural network (ANN) as well as different versions of a feature dictionary. In the system, encoded inputs for the ANN can be decoded by the feature dictionary, which allows for encoded input to be sent to a master version of the ANN over a network instead of an original version of the input which usually includes more data than the encoded input. Thus, by using the feature dictionary for training of a master ANN there can be reduction of data transmission.

    Memory Management Unit (MMU) for Accessing Borrowed Memory

    公开(公告)号:US20210342274A1

    公开(公告)日:2021-11-04

    申请号:US17375455

    申请日:2021-07-14

    Abstract: Systems, methods and apparatuses to accelerate accessing of borrowed memory over network connection are described. For example, a memory management unit (MMU) of a computing device can be configured to be connected both to the random access memory over a memory bus and to a computer network via a communication device. The computing device can borrow an amount of memory from a remote device over a network connection using the communication device; and applications running in the computing device can use virtual memory addresses mapped to the borrowed memory. When a virtual address mapped to the borrowed memory is used, the MMU translates the virtual address into a physical address and instruct the communication device to access the borrowed memory.

    Distributed Computing based on Memory as a Service

    公开(公告)号:US20210263856A1

    公开(公告)日:2021-08-26

    申请号:US17319002

    申请日:2021-05-12

    Abstract: Systems, methods and apparatuses of distributed computing based on Memory as a Service are described. For example, a set of networked computing devices can each be configured to execute an application that accesses memory using a virtual memory address region. Each respective device can map the virtual memory address region to the local memory for a first period of time during which the application is being executed in the respective device, map the virtual memory address region to a local memory of a remote device in the group for a second period of time after starting the application in the respective device and before terminating the application in the respective device, and request the remote device to process data in the virtual memory address region during at least the second period of time.

    Feature dictionary for bandwidth enhancement

    公开(公告)号:US12248412B2

    公开(公告)日:2025-03-11

    申请号:US17841448

    申请日:2022-06-15

    Abstract: A system having multiple devices that can host different versions of an artificial neural network (ANN) as well as different versions of a feature dictionary. In the system, encoded inputs for the ANN can be decoded by the feature dictionary, which allows for encoded input to be sent to a master version of the ANN over a network instead of an original version of the input which usually includes more data than the encoded input. Thus, by using the feature dictionary for training of a master ANN there can be reduction of data transmission.

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