Training convolution neural network on analog resistive processing unit system
US12423567B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 24, 2021 |
| Grant date | Sep 23, 2025 |
| Priority date | — |
| Expiry date | Jul 25, 2044 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06G7/16
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A system comprises an analog resistive processing unit (RPU) system, and one or more processors. The analog RPU system comprises an array of RPU cells. The one or more processors are configured to: configure the analog RPU system to implement a convolutional neural network comprising a convolutional layer comprising at least one kernel matrix; program the at least one array of RPU cells to store a transformed kernel matrix which is generated by applying a first transformation process to the kernel matrix using a first predefined transformation matrix; and utilize the analog RPU system to perform an analog convolution operation by performing analog matrix-vector multiplication operations using the transformed kernel matrix and input vectors of a transformed data matrix, to thereby generate a transformed convolution output matrix, wherein the transformed data matrix is generated by applying a second transformation process to a data matrix using a second predefined transformation matrix.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.