HARDWARE ACCELERATION OF MACHINE LEARNING DESIGNS

    公开(公告)号:US20230401480A1

    公开(公告)日:2023-12-14

    申请号:US17806906

    申请日:2022-06-14

    Applicant: Xilinx, Inc.

    CPC classification number: G06N20/00

    Abstract: Hardware acceleration of machine learning (ML) designs includes translating an ML primitive into an intermediate representation. The intermediate representation is subdivided to specify a functional compute block. The functional compute block is sized according to a compute node primitive adapted for implementing the ML primitive on target hardware. An overlay is generated for the ML primitive, at least in part, by mapping the functional compute block to the compute node primitive. The overlay is synthesizable to implement the ML primitive on the target hardware. The overlay can be scheduled for operation within the target hardware as part of an ML design including the ML primitive.

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