NEURAL NETWORK INSTRUCTION SET ARCHITECTURE
    1.
    发明公开

    公开(公告)号:EP4235509A2

    公开(公告)日:2023-08-30

    申请号:EP23161136.9

    申请日:2017-08-29

    申请人: Google LLC

    IPC分类号: G06N3/04 G06N3/063

    摘要: A computer-implemented method that includes receiving, by a processing unit, an instruction that specifies data values for performing a tensor computation. In response to receiving the instruction, the method may include, performing, by the processing unit, the tensor computation by executing a loop nest comprising a plurality of loops, wherein a structure of the loop nest is defined based on one or more of the data values of the instruction. The tensor computation can be at least a portion of a computation of a neural network layer. The data values specified by the instruction may comprise a value that specifies a type of the neural network layer, and the structure of the loop nest can be defined at least in part by the type of the neural network layer.

    NEURAL NETWORK INSTRUCTION SET ARCHITECTURE
    2.
    发明公开

    公开(公告)号:EP4235509A3

    公开(公告)日:2023-09-20

    申请号:EP23161136.9

    申请日:2017-08-29

    申请人: Google LLC

    IPC分类号: G06N3/04 G06N3/063 G06N3/0464

    摘要: A computer-implemented method that includes receiving, by a processing unit, an instruction that specifies data values for performing a tensor computation. In response to receiving the instruction, the method may include, performing, by the processing unit, the tensor computation by executing a loop nest comprising a plurality of loops, wherein a structure of the loop nest is defined based on one or more of the data values of the instruction. The tensor computation can be at least a portion of a computation of a neural network layer. The data values specified by the instruction may comprise a value that specifies a type of the neural network layer, and the structure of the loop nest can be defined at least in part by the type of the neural network layer.