Systems and methods for a multi-core optimized recurrent neural network
US10832120B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 5, 2016 |
| Grant date | Nov 10, 2020 |
| Priority date | — |
| Expiry date | Aug 15, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/088
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods for a multi-core optimized Recurrent Neural Network (RNN) architecture are disclosed. The various architectures affect communication and synchronization operations according to the Multi-Bulk-Synchronous-Parallel (MBSP) model for a given processor. The resulting family of network architectures, referred to as MBSP-RNNs, perform similarly to a conventional RNNs having the same number of parameters, but are substantially more efficient when mapped onto a modern general purpose processor. Due to the large gain in computational efficiency, for a fixed computational budget, MBSP-RNNs outperform RNNs at applications such as end-to-end speech recognition.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.