About the project

 

SkyANN presents a groundbreaking paradigm for neuromorphic computing. We closely emulate the neurophysiology of the brain by combining skyrmionic quasiparticles with electrical CMOS connections. The skyrmions mimic neurotransmitters and facilitate complex computations at the synapse level, while electrical CMOS connections simulate the propagation of action potentials among neurons for rapid and dense inter-layer connectivity.

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Targeting low-power neuromorphic computing, our innovative magneto-electric devices aim to achieve an energy consumption that is four orders of magnitude lower than the current CMOS technology while doubling the bandwidth for the same device footprint. This will enhance edge inference and learning capabilities. This approach challenges contemporary neural networks implemented with CMOS digital, mixed-signal, and emerging in-memory computing technologies, which are limited by lower energy efficiency and reliability.

 

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