# Universal Memcomputing Machines

@article{Traversa2015UniversalMM, title={Universal Memcomputing Machines}, author={Fabio L. Traversa and Massimiliano Di Ventra}, journal={IEEE Transactions on Neural Networks and Learning Systems}, year={2015}, volume={26}, pages={2702-2715} }

We introduce the notion of universal memcomputing machines (UMMs): a class of brain-inspired general-purpose computing machines based on systems with memory, whereby processing and storing of information occur on the same physical location. We analytically prove that the memory properties of UMMs endow them with universal computing power (they are Turing-complete), intrinsic parallelism, functional polymorphism, and information overhead, namely, their collective states can support exponential…

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## 104 Citations

Memcomputing NP-complete problems in polynomial time using polynomial resources and collective states

- Computer ScienceScience Advances
- 2015

This work shows an experimental demonstration of an actual memcomputing architecture that solves the NP-complete version of the subset sum problem in only one step and is composed of a number of memprocessors that scales linearly with the size of the problem.

On the Universality of Memcomputing Machines

- Computer ScienceIEEE Transactions on Neural Networks and Learning Systems
- 2019

Universal memcomputing machines (UMMs) represent a novel computational model in which memory (time nonlocality) accomplishes both tasks of storing and processing of information. UMMs have been shown…

Memcomputing: Leveraging memory and physics

- Computer Science
- 2019

The literature surrounding a novel hybrid analog-digital computing system (a memcomputer) built from memristors, a basic electronics component with variable resistance, theorized about in 1971 and used recently for various applications including fast non-volatile RAM.

Stress-Testing Memcomputing on Hard Combinatorial Optimization Problems

- Computer ScienceIEEE Transactions on Neural Networks and Learning Systems
- 2020

The simulations of DMMs still scale linearly in both time and memory up to these very large problem sizes versus the exponential requirements of the state-of-the-art solvers, which further reinforce the advantages of the physics-based memcomputing approach compared with traditional ones.

Memcomputing: Leveraging memory and physics to compute efficiently

- Computer ScienceArXiv
- 2018

This work discusses how to employ one such property, memory (time non-locality), in a novel physics-based approach to computation: Memcomputing, and focuses on digital memcomputing machines that are scalable.

Polynomial-time solution of prime factorization and NP-complete problems with digital memcomputing machines.

- Computer ScienceChaos
- 2017

It is proved mathematically that periodic orbits and strange attractors cannot coexist with equilibria, and the implications of the DMM realization through SOLCs to the NP = P question related to constraints of poly-resources resolvability are discussed.

Memcomputing for Accelerated Optimization

- Computer ScienceArXiv
- 2020

This work discusses self-organizing gates, namely Self-Organizing Algebraic Gates (SOAGs), aimed to solve linear inequalities and therefore used to solve optimization problems in Integer Linear Programming (ILP) format.

MemComputing: An efficient topological computing paradigm

- Computer Science2017 IEEE International Conference on Microwaves, Antennas, Communications and Electronic Systems (COMCAS)
- 2017

This work introduces memcomputing, a novel computing paradigm that employs memory (time non-locality) to both store and process information on the same physical location to solve complex problems very efficiently both in hardware and in software.

MemComputing Integer Linear Programming

- Computer ScienceArXiv
- 2018

This work proposes a radically different non-algorithmic approach to ILP based on a novel physics-inspired computing paradigm: Memcomputing, and describes a new circuit architecture of memcomputing machines specifically designed to solve for the linear inequalities representing a general ILP problem.

A Survey and Discussion of Memcomputing Machines

- Computer ScienceArXiv
- 2017

It is argued that the UMM is a physically implausible machine, and that the DMM model, as described by numerical simulations, is no more powerful than Turing-complete computation.

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