Method and device for parallel processing in model training
US9508347B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 16, 2013 |
| Grant date | Nov 29, 2016 |
| Priority date | — |
| Expiry date | Nov 5, 2034 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L15/16
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method and a device for training a DNN model includes: at a device including one or more processors and memory: establishing an initial DNN model; dividing a training data corpus into a plurality of disjoint data subsets; for each of the plurality of disjoint data subsets, providing the data subset to a respective training processing unit of a plurality of training processing units operating in parallel, wherein the respective training processing unit applies a Stochastic Gradient Descent (SGD) process to update the initial DNN model to generate a respective DNN sub-model based on the data subset; and merging the respective DNN sub-models generated by the plurality of training processing units to obtain an intermediate DNN model, wherein the intermediate DNN model is established as either the initial DNN model for a next training iteration or a final DNN model in accordance with a preset convergence condition.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.