Hybrid aggregation for deep learning neural networks
US10783437B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 5, 2017 |
| Grant date | Sep 22, 2020 |
| Priority date | — |
| Expiry date | Jun 19, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/098
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A processing unit topology of a neural network including a plurality of processing units is determined. The neural network includes at least one machine in which each machine includes a plurality of nodes, and wherein each node includes at least one of the plurality of processing units. One or more of the processing units are grouped into a first group according to a first affinity. The first group is configured, using a processor and a memory, to use a first aggregation procedure for exchanging model parameters of a model of the neural network between the processing units of the first group. One or more of the processing units are grouped into a second group according to a second affinity. The second group is configured to use a second aggregation procedure for exchanging the model parameters between the processing units of the second group.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.