Floating-point unit stochastic rounding for accelerated deep learning
US11449574B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 13, 2018 |
| Grant date | Sep 20, 2022 |
| Priority date | — |
| Expiry date | Nov 29, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Techniques in advanced deep learning provide improvements in one or more of accuracy, performance, and energy efficiency. An array of processing elements comprising a portion of a neural network accelerator performs flow-based computations on wavelets of data. Each processing element has a respective compute element and a respective routing element. Each compute element has a respective floating-point unit enabled to perform stochastic rounding, thus in some circumstances enabling reducing systematic bias in long dependency chains of floating-point computations. The long dependency chains of floating-point computations are performed, e.g., to train a neural network or to perform inference with respect to a trained neural network.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.