Invention Grant
- Patent Title: Low resource computational block for a trained neural network
-
Application No.: US16900658Application Date: 2020-06-12
-
Publication No.: US12033070B2Publication Date: 2024-07-09
- Inventor: Xinlin Li , Vahid Partovi Nia
- Applicant: Xinlin Li , Vahid Partovi Nia
- Applicant Address: CA Montreal
- Assignee: HUAWEI TECHNOLOGIES CO., LTD.
- Current Assignee: HUAWEI TECHNOLOGIES CO., LTD.
- Current Assignee Address: CN Shenzhen
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06N3/04 ; G06N3/045 ; G06N3/063 ; G06N3/084 ; G06N20/00 ; G06V10/44 ; G06V10/82 ; G06V30/18

Abstract:
A computational block configured to perform an inference task by applying a plurality of low resource computing operations to a binary input feature tensor to generate an integer feature tensor that is equivalent to an output of multiplication and accumulation operations performed in respect of a ternary weight tensor and the binary input feature tensor; and performing a comparison operation between the generated integer feature tensor and a comparison threshold to generate a binary output feature tensor. The plurality of low resource computing operations are applied to the binary input feature tensor using first and second weight tensors that each include n binary elements and that collectively represent a respective n elements of the ternary weight tensor
Public/Granted literature
- US20210390386A1 LOW RESOURCE COMPUTATIONAL BLOCK FOR A TRAINED NEURAL NETWORK Public/Granted day:2021-12-16
Information query