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arXiv · 1804.03228

Data Driven Optimizations for MTJ based Stochastic Computing

Ankit Mondal·Ankur Srivastava
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Abstract

Stochastic computing, a form of computation with probabilities, presents an alternative to conventional arithmetic units. Magnetic Tunnel Junctions (MTJs), which exhibit probabilistic switching, have been explored as Stochastic Number Generators (SNGs). We provide a perspective of the energy requirements of such an application and design an energy-efficient and data-sensitive MTJ-based SNG. We discuss its benefits when used for stochastic computations, illustrating with the help of a multiplier circuit, in terms of energy savings when compared to computing with the baseline MTJ-SNG.

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Ankit Mondal, Ankur Srivastava. 2018-04-09. Data Driven Optimizations for MTJ based Stochastic Computing. https://arxiv.org/abs/1804.03228

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