METHOD OF SLICING DEEP LEARNING MODEL FOR HETEROGENEOUS EMBEDDED SYSTEM AND INFERENCING METHOD BASED ON SLICED DEEP LEARNING MODEL IN HETEROGENEOUS EMBEDDED SYSTEM

    公开(公告)号:US20230206074A1

    公开(公告)日:2023-06-29

    申请号:US17988322

    申请日:2022-11-16

    CPC classification number: G06N3/082 G06F11/3062

    Abstract: A method of slicing a deep learning model for a heterogeneous embedded system includes collecting, by a model slicing apparatus, an execution time and power consumption when each layer corresponding to one layer of a deep learning model including a plurality of layers is executed in each computing device of the heterogeneous embedded system, predicting, by the model slicing apparatus, a performance cost and a power cost when each of the layers is executed in each of the computing devices using the execution time and the power consumption, predicting, by the model slicing apparatus, a communication cost when transmitting information from each of the layers to a next layer in each of the computing devices, and slicing, by the model slicing apparatus, the plurality of layers so that different sliced layers are allocated to each of the computing devices based on the performance cost, the power cost, and the communication cost in a given execution time limit condition using a reinforcement learning model.

    Apparatus and method for controlling stability of unmanned aerial vehicle

    公开(公告)号:US10562622B2

    公开(公告)日:2020-02-18

    申请号:US15415969

    申请日:2017-01-26

    Abstract: The present invention provides an unmanned aerial vehicle that can maintain stability by changing positions of rotating rotors when one of the rotating rotors malfunctions, and a method for controlling stability of the unmanned aerial vehicle. The unmanned aerial vehicle includes: a main body; a plurality of support bars that are arranged while forming an angle with each other along a circumferential direction of the main body and extended to an outer side from the main body; a plurality of rotating rotors that are respectively provided to the support bars and generate thrust; motors that are respectively connected to the rotating rotors to drive the rotating rotors; drivers that change positions of the respective rotating rotors along the circumferential direction of the main body by moving the support bars with respect to the main body; and a controller that maintains horizontal stability of the main body by controlling the drivers.

    Lightweight architecture for aliased memory operations

    公开(公告)号:US10223261B2

    公开(公告)日:2019-03-05

    申请号:US15393526

    申请日:2016-12-29

    Abstract: A lightweight architecture for an aliased memory operation includes loading data by performing an aliased memory operation, and storing data by performing an aliased memory operation, the loading of data by performed by an aliased memory operation that includes: requesting an aliased address through an HAT without a specific operation for converting an address by means of a CPU processor, converting an address input through the HAT into an aliased address in response to the request for an aliased address, stopping the aliased memory operation through the HAT and calling up a miss handler when the conversion of an address into an aliased address in response to the request for an aliased address fails, and loading data by accessing an SAT using the aliased address when conversion of an address into an aliased address succeeds.

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