System and method of input alignment for efficient vector operations in an artificial neural network
US11238334B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 12, 2019 |
| Grant date | Feb 1, 2022 |
| Priority date | — |
| Expiry date | Dec 26, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/08
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A novel and useful system and method of input alignment for streamlining vector operations that reduce the required memory read bandwidth. The input aligner as deployed in the NN processor, functions to facilitate the reuse of data read from memory and to avoid having to re-read that data in the context of neural network calculations. The input aligner functions to distribute input data (or weights) to the appropriate compute elements while consuming input data in a single cycle. Thus, the input aligner is operative to lower the required read bandwidth of layer input in an ANN. This reflects the fact that normally in practice, a vector multiplication is performed every time instance. This considers the fact that in many native calculations that take place in an ANN, the same data point is involved in multiple calculations.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.