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Memcomputing: a brain-inspired memory-enabled computing paradigm

Which features make the brain such a powerful and energy-efficient computing machine? Can we reproduce them in the solid state, and if so, what type of computing paradigm we would obtain? I will show that a machine that uses memory to both process and store information, like our brain, and is endowed with intrinsic parallelism and information overhead - namely takes advantage, via its collective state, of the network topology related to the problem - has a computational power far beyond our standard digital computers. We have named this novel computing paradigm "memcomputing". As an example, I will show the polynomial-time solution of prime factorization and the NP-hard version of the subset-sum problem using polynomial resources and self-organizable logic gates, namely gates that self-organize to satisfy their logical proposition. These are examples of scalable digital memcomputing machines that can be easily realized with available nanotechnology components.

For further information please contact robert.ilic [at] (Robert Ilic), 301-975-2639.

Massimiliano Di Ventra

Department of Physics, University of California San Diego
La Jolla, CA 92093-0319 USA

Created May 12, 2016, Updated September 12, 2016