A new spintronic nonvolatile memory cell analogous to 1T DRAM with non-destructive READ is proposed. The cells can be used as neural computing units. A dual-circuit neural network architecture is proposed to leverage these devices against the complex operations involved in convolutional networks. Simulations based on HSPICE and MATLAB were performed to study the performance of this architecture when classifying images as well as the effect of varying the size and stability of the nanomagnets. The spintronic cells outperform a purely charge-based implementation of the same network, consuming \approx 100 -pJ total energy per image processed.
|Original language||English (US)|
|Number of pages||7|
|Journal||IEEE Journal on Exploratory Solid-State Computational Devices and Circuits|
|State||Published - Dec 2019|
Bibliographical noteFunding Information:
This work was supported by Seagate Technology PLC.
© 2014 IEEE.
- Cellular neural network (CeNN)
- convolutional neural network (CoNN)
- nonvolatile memory