  In this paper, the intrinsic physical characteristics of spin-orbit torque
(SOT) magnetoresistive random-access memory (MRAM) devices are leveraged to
realize sigmoidal neurons in neuromorphic architectures. Performance
comparisons with the previous power- and area-efficient sigmoidal neuron
circuits exhibit 74x and 12x reduction in power-area-product values for the
proposed SOT-MRAM based neuron. To verify the functionally of the proposed
neuron within larger scale designs, we have implemented a circuit realization
of a 784x16x10 SOT-MRAM based multiplayer perceptron (MLP) for MNIST pattern
recognition application using SPICE circuit simulation tool. The results
obtained exhibit that the proposed SOT-MRAM based MLP can achieve accuracies
comparable to an ideal binarized MLP architecture implemented on GPU, while
realizing orders of magnitude increase in processing speed.
