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In this paper, the intrinsic physical characteristics of spin-orbit torque(SOT) magnetoresistive random-access memory (MRAM) devices are leveraged torealize sigmoidal neurons in neuromorphic architectures. Performancecomparisons with the previous power- and area-efficient sigmoidal neuroncircuits exhibit 74x and 12x reduction in power-area-product values for theproposed SOT-MRAM based neuron. To verify the functionally of the proposedneuron within larger scale designs, we have implemented a circuit realizationof a 784x16x10 SOT-MRAM based multiplayer perceptron (MLP) for MNIST patternrecognition application using SPICE circuit simulation tool. The resultsobtained exhibit that the proposed SOT-MRAM based MLP can achieve accuraciescomparable to an ideal binarized MLP architecture implemented on GPU, whilerealizing orders of magnitude increase in processing speed.

SOT-MRAM based Sigmoidal Neuron for Neuromorphic Architectures