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In-situ Stochastic Training of MTJ Crossbar based Neural Networks
Owing to high device density, scalability and non-volatility, Magnetic Tunnel Junction-based crossbars have garnered significant interest for implementing the weights of an artificial neural network.
Power Optimizations in MTJ-based Neural Networks through Stochastic Computing
In this work, we propose an energy-efficient use of MTJs, which exhibit probabilistic switching behavior, as Stochastic Number Generators (SNGs), which forms the basis of our NN implementation in the SC domain.
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