公开(公告)号：US20230252264A1

公开(公告)日：2023-08-10

申请号：US17669301

申请日：2022-02-10

Applicant: Arm Limited

Inventor： Daren Croxford ,  Rachel Jean Trimble ,  Sharjeel Saeed ,  Roberto Lopez Mendez

IPC: G06N3/04 ,  G06V10/82

CPC classification number: G06N3/04 ,  G06V10/82

Abstract: When executing a neural network comprising a sequence of plural layers of neural network processing in which at least one of the layers of the sequence of plural layers of the neural network is followed by two or more branches of neural network processing, each branch comprising a different sequence of one or more layers of neural network processing, the branch or branches to use for the neural network processing following the layer of the neural network that is followed by the two or more branches of neural network processing is selected based on a property or properties of the output feature map from the layer that is followed by the two or more branches.

公开(公告)号：US11663107B2

公开(公告)日：2023-05-30

申请号：US16797530

申请日：2020-02-21

Applicant: Arm Limited

Inventor： Elliot Maurice Simon Rosemarine ,  Rachel Jean Trimble

IPC: G06F11/34 ,  G06N3/063 ,  G06F9/30 ,  G06F9/38 ,  G06F18/214

CPC classification number: G06F11/3409 ,  G06F9/30098 ,  G06F9/3867 ,  G06F18/214 ,  G06N3/063

Abstract: A computer implemented method, performed in a data processing system comprising a performance monitoring unit. The method comprises receiving a set of computer-readable instructions to be executed by the data processing system to implement at least a portion of a neural network, wherein one or more of the instructions is labeled with one or more performance monitoring labels based upon one or more features of the neural network. The method further comprises configuring the performance monitoring unit to count one or more events occurring in one or more components of the data processing system based on the one or more performance monitoring labels.

公开(公告)号：US12299567B2

公开(公告)日：2025-05-13

申请号：US17479257

申请日：2021-09-20

Applicant: Arm Limited

Inventor： Daren Croxford ,  Sharjeel Saeed ,  Rachel Jean Trimble

IPC: G06N3/04 ,  G06F18/10 ,  G06F18/211 ,  G06N3/0464 ,  G06N3/08 ,  G06V10/75

Abstract: There is provided a data processing apparatus for performing machine learning. The data processing apparatus includes convolution circuitry for convolving a plurality of neighbouring regions of input data using a kernel to produce convolution outputs. Max-pooling circuitry determines and selects the largest of the convolution outputs as a pooled output and prediction circuitry performs a size prediction of the convolution outputs based on the neighbouring regions, wherein the size prediction is performed prior to the max-pooling circuitry determining the largest of the convolution outputs and adjusts a behaviour of the convolution circuitry based on the size prediction.

公开(公告)号：US20230316063A1

公开(公告)日：2023-10-05

申请号：US17708474

申请日：2022-03-30

Applicant: Arm Limited

Inventor： Rachel Jean Trimble ,  Sharjeel Saeed ,  Daren Croxford

IPC: G06N3/08 ,  G06N3/04 ,  G06K9/62

CPC classification number: G06N3/08 ,  G06N3/04 ,  G06K9/6201

Abstract: An input data array is subjected to neural network processing to generate a result of the neural network processing for the input data array. A perturbation is applied to a part (but not all of) the input data array, with neural network processing then performed using the so-perturbed version of the input data array. However only some (and not all) of the perturbed version is subjected to neural network processing, based on the part of the input data array to which the perturbation has been applied. The result of the neural network processing of the perturbed version of the input data array is compared with the result of the neural network processing of the input data array without the perturbation, to determine whether the perturbation of the input data array has an effect on the result of the neural network processing.