Convolutional neural network optimization mechanism

US12020135B2 · kind B2 · utility

Assignee

• Intel Corporation · US

Inventors

• Liwei Ma · Beijing, CN
• Elmoustapha Ould-Ahmed-Vall · Chandler, US
• Barath Lakshmanan · Chandler, US
• Ben J. Ashbaugh · Folsom, US
• Jingyi Jin · Folsom, US
• Jeremy Bottleson · Rancho Cordova, US
• Mike B. Macpherson · Portland, US
• Kevin Nealis · San Jose, US
• Dhawal Srivastava · Phoenix, US
• Joydeep Ray · Folsom, US
• Ping T. Tang · Edison, US
• Michael S. Strickland · Sunnyvale, US
• Xiaoming Chen · Xi'an, CN
• Anbang Yao · Beijing, CN
• Tatiana Shpeisman · Menlo Park, US
• Altug Koker · Cameron Park, US
• Abhishek R. Appu · Cameron Park, US

Key dates

• Filing date: Aug 26, 2021
• Grant date: Jun 25, 2024
• Expiry date: Aug 26, 2042

Classification

• Technology area (CPC G): Physics
• CPC primary: G06N3/045
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

A library of machine learning primitives is provided to optimize a machine learning model to improve the efficiency of inference operations. In one embodiment a trained convolutional neural network (CNN) model is processed into a trained CNN model via pruning, convolution window optimization, and quantization.