公开(公告)号：US20190065943A1

公开(公告)日：2019-02-28

申请号：US16168135

申请日：2018-10-23

Applicant: Google LLC

Inventor： Pierre-Luc Cantin ,  Olivier Temam

IPC: G06N3/063 ,  G06N3/04

Abstract: A circuit for performing neural network computations for a neural network is described. The circuit includes plurality of neural network layers each including a crossbar arrays. The plurality of crossbar arrays are formed in a common substrate in a stacked configuration. Each crossbar array includes a set of crosspoint devices. A respective electrical property of each of the crosspoint devices is adjustable to represent a weight value that is stored for each respective crosspoint device. A processing unit is configured to adjust the respective electrical properties of each of the crosspoint devices by pre-loading each of the crosspoint devices with a tuning signal. A value of the turning signal for each crosspoint device is a function of the weight value represented by each respective crosspoint device.

公开(公告)号：US20190050719A1

公开(公告)日：2019-02-14

申请号：US16059578

申请日：2018-08-09

Applicant: Google LLC

Inventor： Pierre-Luc Cantin ,  Olivier Temam

IPC: G06N3/063 ,  G06F9/50 ,  G06N3/08 ,  G06N3/04 ,  G06F17/16

Abstract: A computing unit for accelerating a neural network is disclosed. The computing unit may include an input unit that includes a digital-to-analog conversion unit and an analog-to-digital conversion unit that is configured to receive an analog signal from the output of a last interconnected analog crossbar circuit of a plurality of analog crossbar circuits and convert the second analog signal into a digital output vector, and a plurality of interconnected analog crossbar circuits that include the first interconnected analog crossbar circuit and the last interconnected crossbar circuits, wherein a second interconnected analog crossbar circuit of the plurality of interconnected analog crossbar circuits is configured to receive a third analog signal from another interconnected analog crossbar circuit of the plurality of interconnected crossbar circuits and perform one or more operations on the third analog signal based on the matrix weights stored by the crosspoints of the second interconnected analog crossbar.

公开(公告)号：US20180285316A1

公开(公告)日：2018-10-04

申请号：US15477791

申请日：2017-04-03

Applicant: Google LLC

Inventor： Gregory Michael Thorson ,  Andrew Everett Phelps ,  Olivier Temam

IPC: G06F15/80 ,  G06F9/30

CPC classification number: G06F15/8053 ,  G06F9/3001 ,  G06F9/30036 ,  G06F9/3877 ,  G06F9/3897 ,  G06F17/10 ,  G06N3/02

Abstract: A vector reduction circuit configured to reduce an input vector of elements comprises a plurality of cells, wherein each of the plurality of cells other than a designated first cell that receives a designated first element of the input vector is configured to receive a particular element of the input vector, receive, from another of the one or more cells, a temporary reduction element, perform a reduction operation using the particular element and the temporary reduction element, and provide, as a new temporary reduction element, a result of performing the reduction operation using the particular element and the temporary reduction element. The vector reduction circuit also comprises an output circuit configured to provide, for output as a reduction of the input vector, a new temporary reduction element corresponding to a result of performing the reduction operation using a last element of the input vector.

公开(公告)号：US20180121786A1

公开(公告)日：2018-05-03

申请号：US15336216

申请日：2016-10-27

Applicant: Google LLC

Inventor： Ravi Narayanaswami ,  Dong Hyuk Woo ,  Olivier Temam ,  Harshit Khaitan

IPC: G06N3/04

CPC classification number: G06N3/04 ,  G06F13/28 ,  G06N3/0454 ,  G06N3/063

Abstract: A computer-implemented method that includes receiving, by a processing unit, an instruction that specifies data values for performing a tensor computation. In response to receiving the instruction, the method may include, performing, by the processing unit, the tensor computation by executing a loop nest comprising a plurality of loops, wherein a structure of the loop nest is defined based on one or more of the data values of the instruction. The tensor computation can be at least a portion of a computation of a neural network layer. The data values specified by the instruction may comprise a value that specifies a type of the neural network layer, and the structure of the loop nest can be defined at least in part by the type of the neural network layer.

公开(公告)号：US20240232603A1

公开(公告)日：2024-07-11

申请号：US18612881

申请日：2024-03-21

Applicant: Google LLC

Inventor： Pierre-Luc Cantin ,  Olivier Temam

IPC: G06N3/065 ,  G06F9/50 ,  G06F17/16 ,  G06N3/04 ,  G06N3/08

CPC classification number: G06N3/065 ,  G06F9/5027 ,  G06F17/16 ,  G06N3/04 ,  G06N3/08

Abstract: A computing unit for accelerating a neural network is disclosed. The computing unit include an input unit that includes a digital-to-analog conversion unit and an analog-to-digital conversion unit that is configured to receive an analog signal from the output of a last interconnected analog crossbar circuit of a plurality of analog crossbar circuits and convert the second analog signal into a digital output vector, and a plurality of interconnected analog crossbar circuits that include the first interconnected analog crossbar circuit and the last interconnected crossbar circuits, wherein a second interconnected analog crossbar circuit of the plurality of interconnected analog crossbar circuits is configured to receive a third analog signal from another interconnected analog crossbar circuit of the plurality of interconnected crossbar circuits and perform one or more operations on the third analog signal based on the matrix weights stored by the crosspoints of the second interconnected analog crossbar.

公开(公告)号：US11966833B2

公开(公告)日：2024-04-23

申请号：US16059578

申请日：2018-08-09

Applicant: Google LLC

Inventor： Pierre-Luc Cantin ,  Olivier Temam

IPC: G06N3/063 ,  G06F9/50 ,  G06F17/16 ,  G06N3/04 ,  G06N3/065 ,  G06N3/08

CPC classification number: G06N3/065 ,  G06F9/5027 ,  G06F17/16 ,  G06N3/04 ,  G06N3/08

Abstract: A computing unit for accelerating a neural network is disclosed. The computing unit may include an input unit that includes a digital-to-analog conversion unit and an analog-to-digital conversion unit that is configured to receive an analog signal from the output of a last interconnected analog crossbar circuit of a plurality of analog crossbar circuits and convert the second analog signal into a digital output vector, and a plurality of interconnected analog crossbar circuits that include the first interconnected analog crossbar circuit and the last interconnected crossbar circuits, wherein a second interconnected analog crossbar circuit of the plurality of interconnected analog crossbar circuits is configured to receive a third analog signal from another interconnected analog crossbar circuit of the plurality of interconnected crossbar circuits and perform one or more operations on the third analog signal based on the matrix weights stored by the crosspoints of the second interconnected analog crossbar.

公开(公告)号：US11948060B2

公开(公告)日：2024-04-02

申请号：US17570784

申请日：2022-01-07

Applicant: GOOGLE LLC

Inventor： Andreas Georg Nowatzyk ,  Olivier Temam ,  Ravi Narayanaswami ,  Uday Kumar Dasari

IPC: G06N3/04 ,  G06N3/045 ,  G06N3/063 ,  H04B1/16

CPC classification number: G06N3/04 ,  G06N3/045 ,  G06N3/063 ,  H04B1/16

Abstract: A three dimensional neural network accelerator that includes a first neural network accelerator tile that includes a first transmission coil, and a second neural network accelerator tile that includes a second transmission coil, wherein the first neural network accelerator tile is adjacent to and aligned vertically with the second neural network accelerator tile, and wherein the first transmission coil is configured to wirelessly communicate with the second transmission coil via inductive coupling.

公开(公告)号：US11836598B2

公开(公告)日：2023-12-05

申请号：US17213871

申请日：2021-03-26

Applicant: Google LLC

Inventor： Andreas Georg Nowatzyk ,  Olivier Temam

IPC: G06N3/04 ,  G06F1/14 ,  G06N3/045 ,  G06N3/063 ,  G06F11/20 ,  G06F11/14 ,  H04L45/02 ,  H04L45/28 ,  H02J50/10 ,  H04L12/42

CPC classification number: G06N3/045 ,  G06F11/1423 ,  G06F11/2051 ,  G06N3/063 ,  H04L45/06 ,  H04L45/28 ,  H02J50/10 ,  H04L2012/421

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for three-dimensionally stacked neural network accelerators. In one aspect, a method includes obtaining data specifying that a tile from a plurality of tiles in a three-dimensionally stacked neural network accelerator is a faulty tile. The three-dimensionally stacked neural network accelerator includes a plurality of neural network dies, each neural network die including a respective plurality of tiles, each tile has input and output connections. The three-dimensionally stacked neural network accelerator is configured to process inputs by routing the input through each of the plurality of tiles according to a dataflow configuration and modifying the dataflow configuration to route an output of a tile before the faulty tile in the dataflow configuration to an input connection of a tile that is positioned above or below the faulty tile on a different neural network die than the faulty tile.

公开(公告)号：US11727259B2

公开(公告)日：2023-08-15

申请号：US17985061

申请日：2022-11-10

Applicant: Google LLC

Inventor： Olivier Temam ,  Harshit Khaitan ,  Ravi Narayanaswami ,  Dong Hyuk Woo

IPC: G06N3/063 ,  G06F13/00 ,  G06N3/045 ,  G06N3/048 ,  G06F9/38 ,  G06F17/16

CPC classification number: G06N3/063 ,  G06F9/3887 ,  G06F9/3895 ,  G06F13/00 ,  G06F17/16 ,  G06N3/045 ,  G06N3/048

Abstract: One embodiment of an accelerator includes a computing unit; a first memory bank for storing input activations and a second memory bank for storing parameters used in performing computations, the second memory bank configured to store a sufficient amount of the neural network parameters on the computing unit to allow for latency below a specified level with throughput above a specified level. The computing unit includes at least one cell comprising at least one multiply accumulate (“MAC”) operator that receives parameters from the second memory bank and performs computations. The computing unit further includes a first traversal unit that provides a control signal to the first memory bank to cause an input activation to be provided to a data bus accessible by the MAC operator. The computing unit performs computations associated with at least one element of a data array, the one or more computations performed by the MAC operator.

公开(公告)号：US20210256361A1

公开(公告)日：2021-08-19

申请号：US17186598

申请日：2021-02-26

Applicant: Google LLC

Inventor： Uday Kumar Dasari ,  Olivier Temam ,  Ravi Narayanaswami ,  Dong Hyuk Woo

IPC: G06N3/063 ,  G06N3/04 ,  G06F15/78

Abstract: Apparatus and methods for processing neural network models are provided. The apparatus can comprise a plurality of identical artificial intelligence processing dies. Each artificial intelligence processing die among the plurality of identical artificial intelligence processing dies can include at least one inter-die input block and at least one inter-die output block. Each artificial intelligence processing die among the plurality of identical artificial intelligence processing dies is communicatively coupled to another artificial intelligence processing die among the plurality of identical artificial intelligence processing dies by way of one or more communication paths from the at least one inter-die output block of the artificial intelligence processing die to the at least one inter-die input block of the artificial intelligence processing die. Each artificial intelligence processing die among the plurality of identical artificial intelligence processing dies corresponds to at least one layer of a neural network.