End-to-end data format selection for hardware implementation of deep neural networks
US12020145B2 · kind B2 · utility
Assignee
Inventor
Key dates
| Filing date | Nov 5, 2018 |
| Grant date | Jun 25, 2024 |
| Priority date | — |
| Expiry date | Dec 10, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/045
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods for selecting fixed point number formats for representing values input to and/or output from layers of a DNN which take into account the impact of the fixed point number formats for a particular layer in the context of the DNN. The methods comprise selecting the fixed point number format(s) used to represent sets of values input to and/or output from a layer one layer at a time in a predetermined sequence wherein any layer is preceded in the sequence by the layer(s) from which it depends. The fixed point number format(s) for each layer is/are selected based on the error in the output of the DNN associated with the fixed point number formats. Once the fixed point number format(s) for a layer has/have been selected any calculation of the error in the output of the DNN for a subsequent layer in the sequence is based on that layer being configured to use the selected fixed point number formats.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.