PROGRAMMABLE NON-LINEAR ACTIVATION ENGINE FOR NEURAL NETWORK ACCELERATION

    公开(公告)号:US20230297824A1

    公开(公告)日:2023-09-21

    申请号:US17655489

    申请日:2022-03-18

    Applicant: Xilinx, Inc.

    CPC classification number: G06N3/08

    Abstract: A programmable, non-linear (PNL) activation engine for a neural network is capable of receiving input data within a circuit. In response to receiving an instruction corresponding to the input data, the PNL activation engine is capable of selecting a first non-linear activation function from a plurality of non-linear activation functions by decoding the instruction. The PNL activation engine is capable of fetching a first set of coefficients corresponding to the first non-linear activation function from a memory. The PNL activation engine is capable of performing a polynomial approximation of the first non-linear activation function on the input data using the first set of coefficients. The PNL activation engine is capable of outputting a result from the polynomial approximation of the first non-linear activation function.

    Instruction set architecture for data processing array control

    公开(公告)号:US12248786B2

    公开(公告)日:2025-03-11

    申请号:US17818309

    申请日:2022-08-08

    Applicant: Xilinx, Inc.

    Abstract: Controlling a data processing (DP) array includes creating a replica of a register address space of the DP array based on the design and the DP array. A sequence of instructions, including write instructions and read instructions, is received. The write instructions correspond to buffer descriptors specifying runtime data movements for a design for a DP array. The write instructions are converted into transaction instructions and the read instructions are converted into wait instructions based on the replica of the register address space. The transaction instructions and the wait instructions are included in an instruction buffer. The instruction buffer is provided to a microcontroller configured to execute the transaction instructions and the wait instructions to implement the runtime data movements for the design as implemented in the DP array. In another aspect, the instruction buffer is stored in a file for subsequent execution by the microcontroller.

    Scalable acceleration of reentrant compute operations

    公开(公告)号:US12147379B2

    公开(公告)日:2024-11-19

    申请号:US18089780

    申请日:2022-12-28

    Applicant: XILINX, INC.

    Abstract: Examples herein describe techniques for performing parallel processing using a plurality of processing elements (PEs) and a controller for data that has data dependencies. For example, a calculation may require an entire row or column to be summed, or to determine its mean. The PEs can be assigned different chunks of a data set (e.g., a tensor set, a column, or a row) for processing. The PEs can use one or more tokens to inform the controller when they are done with partial processing of their data chunks. The controller can then gather the partial results and determine an intermediate value for the data set. The controller can then distribute this intermediate value to the PEs which then re-process their respective data chunks using the intermediate value to generate final results.

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