Multi-functional execution lane for image processor

    公开(公告)号:US10185560B2

    公开(公告)日:2019-01-22

    申请号:US15591955

    申请日:2017-05-10

    Applicant: Google LLC

    Abstract: An apparatus is described that includes an execution unit having a multiply add computation unit, a first ALU logic unit and a second ALU logic unit. The ALU unit is to perform first, second, third and fourth instructions. The first instruction is a multiply add instruction. The second instruction is to perform parallel ALU operations with the first and second ALU logic units operating simultaneously to produce different respective output resultants of the second instruction. The third instruction is to perform sequential ALU operations with one of the ALU logic units operating from an output of the other of the ALU logic units to determine an output resultant of the third instruction. The fourth instruction is to perform an iterative divide operation in which the first ALU logic unit and the second ALU logic unit operate during to determine first and second division resultant digit values.

    Convolutional neural network on programmable two dimensional image processor

    公开(公告)号:US10789505B2

    公开(公告)日:2020-09-29

    申请号:US15631906

    申请日:2017-06-23

    Applicant: Google LLC

    Abstract: A method is described that includes executing a convolutional neural network layer on an image processor having an array of execution lanes and a two-dimensional shift register. The executing of the convolutional neural network includes loading a plane of image data of a three-dimensional block of image data into the two-dimensional shift register. The executing of the convolutional neural network also includes performing a two-dimensional convolution of the plane of image data with an array of coefficient values by sequentially: concurrently multiplying within the execution lanes respective pixel and coefficient values to produce an array of partial products; concurrently summing within the execution lanes the partial products with respective accumulations of partial products being kept within the two dimensional register for different stencils within the image data; and, effecting alignment of values for the two-dimensional convolution within the execution lanes by shifting content within the two-dimensional shift register array.

    Sheet generator for image processor

    公开(公告)号:US10560598B2

    公开(公告)日:2020-02-11

    申请号:US16291047

    申请日:2019-03-04

    Applicant: Google LLC

    Abstract: A sheet generator circuit is described. The sheet generator includes electronic circuitry to receive a line group of image data including multiple rows of data from a frame of image data. The multiple rows are sufficient in number to encompass multiple neighboring overlapping stencils. The electronic circuitry is to parse the line group into a smaller sized sheet. The electronic circuitry is to load the sheet into a data computation unit having a two dimensional shift array structure coupled to an array of processors.

    Convolutional neural network on programmable two dimensional image processor

    公开(公告)号:US10546211B2

    公开(公告)日:2020-01-28

    申请号:US15201204

    申请日:2016-07-01

    Applicant: Google LLC

    Abstract: A method is described that includes executing a convolutional neural network layer on an image processor having an array of execution lanes and a two-dimensional shift register. The two-dimensional shift register provides local respective register space for the execution lanes. The executing of the convolutional neural network includes loading a plane of image data of a three-dimensional block of image data into the two-dimensional shift register. The executing of the convolutional neural network also includes performing a two-dimensional convolution of the plane of image data with an array of coefficient values by sequentially: concurrently multiplying within the execution lanes respective pixel and coefficient values to produce an array of partial products; concurrently summing within the execution lanes the partial products with respective accumulations of partial products being kept within the two dimensional register for different stencils within the image data; and, effecting alignment of values for the two-dimensional convolution within the execution lanes by shifting content within the two-dimensional shift register array.

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