Invention Application
- Patent Title: HARDWARE ACCELERATOR OPTIMIZED GROUP CONVOLUTION BASED NEURAL NETWORK MODELS
-
Application No.: US18693724Application Date: 2021-10-08
-
Publication No.: US20240386260A1Publication Date: 2024-11-21
- Inventor: Berkin Akin , Suyog Gupta , Cao Gao , Ping Zhou , Gabriel Mintzer Bender , Hanxiao Liu
- Applicant: Google LLC
- Applicant Address: US CA Mountain View
- Assignee: Google LLC
- Current Assignee: Google LLC
- Current Assignee Address: US CA Mountain View
- International Application: PCT/US2021/054148 WO 20211008
- Main IPC: G06N3/063
- IPC: G06N3/063 ; G06N3/0464 ; G06V10/77 ; G06V10/82 ; G06V10/94

Abstract:
Methods, systems, and apparatus, including computer-readable media, are described for processing an input image using integrated circuit that implements a convolutional neural network with a group convolution layer. The processing includes determining a mapping of partitions along a channel dimension of an input feature map to multiply accumulate cells (MACs) in a computational unit of the circuit and applying a group convolution to the input feature map. Applying the group convolution includes, for each partition: providing weights for the group convolution layer to a subset of MACs based on the mapping; providing, via an input bus of the circuit, an input of the feature map to each MAC in the subset; and computing, at each MAC in the subset, a product using the input and a weight for the group convolution layer. An output feature map is generated for the group convolution layer based on an accumulation of products.
Information query