Distributed training of machine learning models
US12423578B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 29, 2022 |
| Grant date | Sep 23, 2025 |
| Priority date | — |
| Expiry date | Jul 25, 2044 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/063
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A resource set which includes multiple servers with a respective plurality of training computing devices is identified for training a machine learning model. The resource set is subdivided into partition groups, such that each partition group can store a respective replica of state information of the model. The model is trained using the partition groups. The training comprises a multi-stage gathering of a portion of the state information at training computing devices of a particular partition group. Different types of communication channels between training computing devices are used in respective stages of the gathering, including inter-server communication channels in one stage and an intra-server communication channel during another stage. A trained version of the model is stored.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.