公开(公告)号：US20200027195A1

公开(公告)日：2020-01-23

申请号：US16531876

申请日：2019-08-05

Applicant: Google LLC

Inventor： Carrell Daniel Killebrew ,  Ravi Narayanaswami ,  Dong Hyuk Woo

IPC: G06T3/40 ,  G06T1/60 ,  G06N20/00

Abstract: Methods, systems, and apparatus, including an apparatus for determining pixel coordinates for image transformation and memory addresses for storing the transformed image data. In some implementations, a system includes a processing unit configured to perform machine learning computations for images using a machine learning model and pixel values for the images, a storage medium configured to store the pixel values for the images, and a memory address computation unit that includes one or more hardware processors. The processor(s) are configured to receive image data for an image and determine that the dimensions of the image do not match the dimensions of the machine learning model. In response, the processor(s) determine pixel coordinates for a transformed version of the input image and, for each of the pixel coordinates, memory address(es), in the storage medium, for storing pixel value(s) that will be used to generate an input to the machine learning model.

公开(公告)号：US20220245453A1

公开(公告)日：2022-08-04

申请号：US17629437

申请日：2020-10-07

Applicant: Google LLC

Inventor： David Alexander Majnemer ,  Ravi Narayanaswami ,  Dong Hyuk Woo ,  Carrell Daniel Killebrew

IPC: G06N3/08

Abstract: Methods, systems, and apparatus, including an apparatus for redistributing tensor elements among computing units are described. In one aspect, a method includes distributing tensor elements of an N-dimensional tensor among multiple computing units of a computation system. Each computing unit redistributes the subset of tensor elements previously distributed to the computing unit to computing units. Each computing unit accesses redistribution partitioning data that specifies, for each computing unit, the tensor elements that are to be stored by the computing unit after redistributing the tensor elements. For each tensor element previously distributed to the particular computing unit, the computing unit determines a global linearized index value for the tensor element based on a multi-dimensional index for the tensor element. The computing unit determines, using the redistribution partitioning data and the global linearized index value, a destination computing unit and sends the tensor element to the destination computing unit.

公开(公告)号：US11170469B2

公开(公告)日：2021-11-09

申请号：US16531876

申请日：2019-08-05

Applicant: Google LLC

Inventor： Carrell Daniel Killebrew ,  Ravi Narayanaswami ,  Dong Hyuk Woo

IPC: G06T3/40 ,  G06T1/60 ,  G06N20/00

Abstract: Methods, systems, and apparatus, including an apparatus for determining pixel coordinates for image transformation and memory addresses for storing the transformed image data. In some implementations, a system includes a processing unit configured to perform machine learning computations for images using a machine learning model and pixel values for the images, a storage medium configured to store the pixel values for the images, and a memory address computation unit that includes one or more hardware processors. The processor(s) are configured to receive image data for an image and determine that the dimensions of the image do not match the dimensions of the machine learning model. In response, the processor(s) determine pixel coordinates for a transformed version of the input image and, for each of the pixel coordinates, memory address(es), in the storage medium, for storing pixel value(s) that will be used to generate an input to the machine learning model.

公开(公告)号：US10373291B1

公开(公告)日：2019-08-06

申请号：US15885178

申请日：2018-01-31

Applicant: Google LLC

Inventor： Carrell Daniel Killebrew ,  Ravi Narayanaswami ,  Dong Hyuk Woo

IPC: G06T1/60 ,  G06F15/18 ,  G06T3/40 ,  G06N20/00

Abstract: Methods, systems, and apparatus, including an apparatus for determining pixel coordinates for image transformation and memory addresses for storing the transformed image data. In some implementations, a system includes a processing unit configured to perform machine learning computations for images using a machine learning model and pixel values for the images, a storage medium configured to store the pixel values for the images, and a memory address computation unit that includes one or more hardware processors. The processor(s) are configured to receive image data for an image and determine that the dimensions of the image do not match the dimensions of the machine learning model. In response, the processor(s) determine pixel coordinates for a transformed version of the input image and, for each of the pixel coordinates, memory address(es), in the storage medium, for storing pixel value(s) that will be used to generate an input to the machine learning model.

公开(公告)号：US20190236755A1

公开(公告)日：2019-08-01

申请号：US15885178

申请日：2018-01-31

Applicant: Google LLC

Inventor： Carrell Daniel Killebrew ,  Ravi Narayanaswami ,  Dong Hyuk Woo

IPC: G06T3/40 ,  G06F15/18 ,  G06T1/60

CPC classification number: G06T3/4007 ,  G06N20/00 ,  G06T1/60

Abstract: Methods, systems, and apparatus, including an apparatus for determining pixel coordinates for image transformation and memory addresses for storing the transformed image data. In some implementations, a system includes a processing unit configured to perform machine learning computations for images using a machine learning model and pixel values for the images, a storage medium configured to store the pixel values for the images, and a memory address computation unit that includes one or more hardware processors. The processor(s) are configured to receive image data for an image and determine that the dimensions of the image do not match the dimensions of the machine learning model. In response, the processor(s) determine pixel coordinates for a transformed version of the input image and, for each of the pixel coordinates, memory address(es), in the storage medium, for storing pixel value(s) that will be used to generate an input to the machine learning model.