Dataflow triggered tasks for accelerated deep learning
US10614357B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 15, 2018 |
| Grant date | Apr 7, 2020 |
| Priority date | — |
| Expiry date | Apr 28, 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 performs flow based computations on wavelets of data. Each processing element has a compute element and a routing element. Each compute element has memory. Each router enables communication via wavelets with nearest neighbors in a 2D mesh. Routing is controlled by respective virtual channel specifiers in each wavelet and routing configuration information in each router. A compute element receives a particular wavelet comprising a particular virtual channel specifier and a particular data element. Instructions are read from the memory of the compute element based at least in part on the particular virtual channel specifier. The particular data element is used as an input operand to execute at least one of the instructions.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.