MemComputing has been featured in the Global Quantum Intelligence report entitled “Quantum Solvers-Optimization”. Although not a quantum computing company, our advanced technology delivers solutions to complex optimization problems that remain intractable for both classical and quantum methods. By leveraging our innovative approach, our partners can achieve operational excellence today, without having to wait for uncertain quantum advancements. To gain a deeper understanding of our technology, we encourage you to explore our website and examine the real-world case studies that validate our technology. Below is the section on MemComputing:
“MemComputing attempts to formalize the general concept of computing with and in memory (or computational memory), as opposed to conventional computing paradigms where the processing unit and memory are assumed physically separated entities exchanging information [1,2]. To study this alternative computing paradigm, they introduced the Universal Memcomputing Machine (UMM) as the abstract model describing the class of non-von Neumann architectures leveraging the computational memory as a central building block. It aims to be equivalent to a non-deterministic Turing machine, hoping to offer efficient solution of non-deterministic polynomial (NP) problems, with particular emphasis on combinatorial optimization.
The challenge is therefore finding a practical realization of a UMM possessing enough requirements to efficiently solve problems that are combinatorial in nature. To this end, they introduced a computational architecture based on Self-Organizing Gates (SOG), called Self-Organizing Circuits (SOCs). Each SOG is designed to reach an equilibrium if and only if a given relation among terminal states is satisfied. For example, if it is a boolean relation, we have a Self-Organizing Logic Gate. Unlike standard logic gates, they exploit the unique properties of being input/output terminal agnostic. Once assembled to form a Self-Organizing Logic Circuit, they take advantage of the collective state of the system to perform a computation. This creates nonlocal long-range correlations that enable fast convergence for solutions of hard combinatorial problems.”
Link to full report: https://my.global-qi.com/1upfjqt/