Patent · US Active

Task activating for accelerated deep learning

US11157806B2 · kind B2 · utility

4Cited by
37References
50Claims
0Family size

Assignee

Inventors

Key dates

Filing dateApr 17, 2018
Grant dateOct 26, 2021
Priority date
Expiry dateApr 17, 2038

Classification

  • Technology area (CPC H)Electricity
  • CPC primaryH04L49/506
  • 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 router enables communication via wavelets with at least nearest neighbors in a 2D mesh. Routing is controlled by virtual channel specifiers in each wavelet and routing configuration information in each router. Execution of an activate instruction or completion of a fabric vector operation activates one of the virtual channels. A virtual channel is selected from a pool comprising previously activated virtual channels and virtual channels associated with previously received wavelets. A task corresponding to the selected virtual channel is activated by executing instructions corresponding to the selected virtual channel.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.