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    ARCHITECTURE FOR HIGH PERFORMANCE, POWER EFFICIENT, PROGRAMMABLE IMAGE PROCESSING
    3.
    发明申请
    ARCHITECTURE FOR HIGH PERFORMANCE, POWER EFFICIENT, PROGRAMMABLE IMAGE PROCESSING 有权
    高性能，高能效，可编程图像处理的架构

    公开(公告)号：US20160314555A1

    公开(公告)日：2016-10-27

    申请号：US14694828

    申请日：2015-04-23

    Applicant: Google Inc.

    Inventor： Qiuling Zhu ,  Ofer Shacham ,  Albert Meixner ,  Jason Rupert Redgrave ,  Daniel Frederic Finchelstein ,  David Patterson ,  Neeti Desai ,  Donald Stark ,  Edward T. Chang ,  William R. Mark

    IPC: G06T1/20 ,  G06T1/60 ,  H04N5/91 ,  H04N5/378

    CPC classification number: G06T1/20 ,  G06T1/60 ,  H04N5/378 ,  H04N5/91

    Abstract: An apparatus is described. The apparatus includes an image processing unit. The image processing unit includes a network. The image processing unit includes a plurality of stencil processor circuits each comprising an array of execution unit lanes coupled to a two-dimensional shift register array structure to simultaneously process multiple overlapping stencils through execution of program code. The image processing unit includes a plurality of sheet generators respectively coupled between the plurality of stencil processors and the network. The sheet generators are to parse input line groups of image data into input sheets of image data for processing by the stencil processors, and, to form output line groups of image data from output sheets of image data received from the stencil processors. The image processing unit includes a plurality of line buffer units coupled to the network to pass line groups in a direction from producing stencil processors to consuming stencil processors to implement an overall program flow.

    Abstract translation: 描述了一种装置。 该装置包括图像处理单元。 图像处理单元包括网络。 图像处理单元包括多个模板处理器电路，每个模板处理器电路各自包括耦合到二维移位寄存器阵列结构的执行单元通道的阵列，以通过执行程序代码来同时处理多个重叠模版。 图像处理单元包括分别耦合在多个模板处理器和网络之间的多个片材生成器。 片材生成器将图像数据的输入线组分解成图像数据的输入片以供模板处理器处理，并且从从模版处理器接收的图像数据的输出片材中形成图像数据的输出线组。 图像处理单元包括耦合到网络的多个行缓冲单元，以在从生成模板处理器到消耗模板处理器的方向上传递线组，以实现整个程序流程。

    Virtual Image Processor Instruction Set Architecture (ISA) And Memory Model And Exemplary Target Hardware Having A Two-Dimensional Shift Array Structure
    4.
    发明申请
    Virtual Image Processor Instruction Set Architecture (ISA) And Memory Model And Exemplary Target Hardware Having A Two-Dimensional Shift Array Structure 审中-公开
    虚拟图像处理器指令集架构（ISA）和具有二维移位阵列结构的存储器模型和示例性目标硬件

    公开(公告)号：US20160313980A1

    公开(公告)日：2016-10-27

    申请号：US14694890

    申请日：2015-04-23

    Applicant: Google Inc.

    Inventor： Albert Meixner ,  Ofer Shacham ,  David Patterson ,  Daniel Frederic Finchelstein ,  Qiuling Zhu ,  Jason Rupert Redgrave

    IPC: G06F9/44 ,  G06F9/30

    CPC classification number: G06F17/5009 ,  G06F8/10 ,  G06F8/20 ,  G06F9/3004 ,  G06F9/30101 ,  G06T1/20 ,  G06T2200/28

    Abstract: A method is described that includes instantiating, within an application software development environment, a virtual processor having an instruction set architecture and memory model that contemplate first and second regions of reserved memory. The first reserved region is to keep data of an input image array. The second reserved region is to keep data of an output image array. The method also includes simulating execution of a memory load instruction of the instruction set architecture by automatically targeting the first reserved region and identifying desired input data with first and second coordinates relative to the virtual processor's position within an orthogonal coordinate system and expressed in the instruction format of the memory load instruction.

    Abstract translation: 描述了一种方法，其包括在应用软件开发环境内实例化具有预期存储器的第一和第二区域的指令集架构和存储器模型的虚拟处理器。 第一个保留区域是保留输入图像数组的数据。 第二保留区域是保留输出图像数组的数据。 该方法还包括通过自动地针对第一保留区域来模拟指令集架构的存储器加载指令的执行，并且相对于虚拟处理器在正交坐标系中的位置识别具有第一和第二坐标的期望输入数据并以指令格式表示 的存储器加载指令。

    CONVOLUTIONAL NEURAL NETWORK ON PROGRAMMABLE TWO DIMENSIONAL IMAGE PROCESSOR
    7.
    发明申请
    CONVOLUTIONAL NEURAL NETWORK ON PROGRAMMABLE TWO DIMENSIONAL IMAGE PROCESSOR 审中-公开

    公开(公告)号：US20180005075A1

    公开(公告)日：2018-01-04

    申请号：US15631906

    申请日：2017-06-23

    Applicant: Google Inc.

    Inventor： Ofer Shacham ,  David Patterson ,  William R. Mark ,  Albert Meixner ,  Daniel Frederic Finchelstein ,  Jason Rupert Redgrave

    IPC: G06K9/56 ,  G06T5/20 ,  G06K9/46

    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.

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