28,909 research outputs found
Reconfigurable nanoelectronics using graphene based spintronic logic gates
This paper presents a novel design concept for spintronic nanoelectronics
that emphasizes a seamless integration of spin-based memory and logic circuits.
The building blocks are magneto-logic gates based on a hybrid
graphene/ferromagnet material system. We use network search engines as a
technology demonstration vehicle and present a spin-based circuit design with
smaller area, faster speed, and lower energy consumption than the
state-of-the-art CMOS counterparts. This design can also be applied in
applications such as data compression, coding and image recognition. In the
proposed scheme, over 100 spin-based logic operations are carried out before
any need for a spin-charge conversion. Consequently, supporting CMOS
electronics requires little power consumption. The spintronic-CMOS integrated
system can be implemented on a single 3-D chip. These nonvolatile logic
circuits hold potential for a paradigm shift in computing applications.Comment: 14 pages (single column), 6 figure
Spin-Based Neuron Model with Domain Wall Magnets as Synapse
We present artificial neural network design using spin devices that achieves
ultra low voltage operation, low power consumption, high speed, and high
integration density. We employ spin torque switched nano-magnets for modelling
neuron and domain wall magnets for compact, programmable synapses. The spin
based neuron-synapse units operate locally at ultra low supply voltage of 30mV
resulting in low computation power. CMOS based inter-neuron communication is
employed to realize network-level functionality. We corroborate circuit
operation with physics based models developed for the spin devices. Simulation
results for character recognition as a benchmark application shows 95% lower
power consumption as compared to 45nm CMOS design
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