Efficient tile mapping for row-by-row convolutional neural network mapping for analog artificial intelligence network inference
US11562240B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 27, 2020 |
| Grant date | Jan 24, 2023 |
| Priority date | — |
| Expiry date | May 22, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/065
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Implementing a convolutional neural network (CNN) includes configuring a crosspoint array to implement a convolution layer in the CNN. Convolution kernels of the layer are stored in crosspoint devices of the array. Computations for the CNN are performed by iterating a set of operations for a predetermined number of times. The operations include transmitting voltage pulses corresponding to a subpart of a vector of input data to the crosspoint array. The voltage pulses generate electric currents that are representative of performing multiplication operations at the crosspoint device based on weight values stored at the crosspoint devices. A set of integrators accumulates an electric charge based on the output electric currents from the respective crosspoint devices. The crosspoint array outputs the accumulated charge after iterating for the predetermined number of times. The accumulated charge represents a multiply-add result of the vector of input data and the one or more convolution kernels.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.