Non Boolean Computing With Spintronic Devices
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Non-Boolean Computing with Spintronic Devices
Author | : Kawsher A. Roxy |
Publisher | : |
Total Pages | : 123 |
Release | : 2018 |
Genre | : Computer engineering |
ISBN | : 9781680833638 |
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In addition to the electron's charge, spintronics deals with the electron's spin and magnetic moment for computation or data storage. Certainly, an extremely promising application of spintronic devices is datastorage; the remanence makes the memory non-volatile and instant-on. Moreover, these devices are thermally stable making them suitable for extreme-temperature operations. In this monograph, we leverage spintronic devices for information processing and do not cover data-storage. We explore three non- Boolean computational framework: (1) Energy minimization based optimizer, which we recently published in Nature Nanotechnology [23], (2) Coupled Oscillatory framework [47] and (3) Neuromorphic learning framework. In Energy minimization framework, we harness the innate physical properties of nanomagnets to directly solve a class of energy minimization problems. Due to the fact that the Hamiltonian of a system of coupled nanomagnets is quadratic, a wide class of quadratic energy minimization can be solved much more quickly by the relaxation of a grid of nanomagnets than by a conventional Boolean processor. Another property that researchers have harnessed is achieving radio-frequency ferromagnetic resonance, which can be harnessed in a system of nano-oscillators to provide solution to dynamical systems. This property is also utilized in neuromorphic frameworks.
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