公开(公告)号：US20220019869A1

公开(公告)日：2022-01-20

申请号：US17039178

申请日：2020-09-30

Applicant: Google LLC

Inventor： Sheng Li ,  Norman Paul Jouppi ,  Quoc V. Le ,  Mingxing Tan ,  Ruoming Pang ,  Liqun Cheng ,  Andrew Li

IPC: G06N3/04 ,  G06N3/08

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining an architecture for a task neural network that is configured to perform a particular machine learning task on a target set of hardware resources. When deployed on a target set of hardware, such as a collection of datacenter accelerators, the task neural network may be capable of performing the particular machine learning task with enhanced accuracy and speed.

公开(公告)号：US20250077833A1

公开(公告)日：2025-03-06

申请号：US18821971

申请日：2024-08-30

Applicant: Google LLC

Inventor： Sheng Li ,  Norman Paul Jouppi ,  Quoc V. Le ,  Mingxing Tan ,  Ruoming Pang ,  Liqun Cheng ,  Andrew Li

IPC: G06N3/04 ,  G06N3/08

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining an architecture for a task neural network that is configured to perform a particular machine learning task on a target set of hardware resources. When deployed on a target set of hardware, such as a collection of datacenter accelerators, the task neural network may be capable of performing the particular machine learning task with enhanced accuracy and speed.

公开(公告)号：US12131244B2

公开(公告)日：2024-10-29

申请号：US17039178

申请日：2020-09-30

Applicant: Google LLC

Inventor： Sheng Li ,  Norman Paul Jouppi ,  Quoc V. Le ,  Mingxing Tan ,  Ruoming Pang ,  Liqun Cheng ,  Andrew Li

IPC: G06N3/04 ,  G06N3/08

CPC classification number: G06N3/04 ,  G06N3/08

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining an architecture for a task neural network that is configured to perform a particular machine learning task on a target set of hardware resources. When deployed on a target set of hardware, such as a collection of datacenter accelerators, the task neural network may be capable of performing the particular machine learning task with enhanced accuracy and speed.

公开(公告)号：US20220230048A1

公开(公告)日：2022-07-21

申请号：US17175029

申请日：2021-02-12

Applicant: Google LLC

Inventor： Andrew Li ,  Sheng Li ,  Mingxing Tan ,  Ruoming Pang ,  Liqun Cheng ,  Quoc V. Le ,  Norman Paul Jouppi

IPC: G06N3/04 ,  G06N3/08

Abstract: Methods, systems, and apparatus, including computer-readable media, for scaling neural network architectures on hardware accelerators. A method includes receiving training data and information specifying target computing resources, and performing using the training data, a neural architecture search over a search space to identify an architecture for a base neural network. A plurality of scaling parameter values for scaling the base neural network can be identified, which can include repeatedly selecting a plurality of candidate scaling parameter values, and determining a measure of performance for the base neural network scaled according to the plurality of candidate scaling parameter values, in accordance with a plurality of second objectives including a latency objective. An architecture for a scaled neural network can be determined using the architecture of the base neural network scaled according to the plurality of scaling parameter values.