  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 about 100 pJ
total per image processed.
