Memcomputing: a computing paradigm to store and process information on the same physical platform

From NextBigFuture.com

Technology Review – The properties of memelements that make them so good at biological computing has been hard to pin down. Which is where Di Ventra and Pershin come in. They have distilled the essential properties that ought to allow memelements to match the brain’s performance.

They say these properties include the ability to store information over long periods; the ability to act collectively so that the state of a memdevice as a whole depends on the states of all its memelements; a robustness against noise and small imperfections; and so on.

Perhaps the most important, however, is the ability to store and process information at the same time, a property that is entirely alien in the conventional computing world

This is an interesting approach that attempts to crystallise the best way to approach memcomputing. And it has huge potential. Memcapacitors and meminductors essentially consume no energy and so ought to allow very low energy applications. That should make it possible for them to approach the energy efficiency of natural systems for the first time.

“An important milestone in this field would be the demonstration of a memcomputing device with computing capabilities and power consumption comparable to (or better than) those of the human brain,” say Di Ventra and Pershin.

Arxiv – Memcomputing: a computing paradigm to store and process information on the same physical platform

In present day technology, storing and processing of information occur on physically distinct regions of space. Not only does this result in space limitations; it also translates into unwanted delays in retrieving and processing of relevant information. There is, however, a class of two-terminal passive circuit elements with memory, memristive, memcapacitive and meminductive systems – collectively called memelements – that perform both information processing and storing of the initial, intermediate and final computational data on the same physical platform. Importantly, the states of these memelements adjust to input signals and provide analog capabilities unavailable in standard circuit elements, resulting in adaptive circuitry, and providing analog massively-parallel computation. All these features are tantalizingly similar to those encountered in the biological realm, thus offering new opportunities for biologically-inspired computation. Of particular importance is the fact that these memelements emerge naturally in nanoscale systems, and are therefore a consequence and a natural by-product of the continued miniaturization of electronic devices. We will discuss the various possibilities offered by memcomputing, discuss the criteria that need to be satisfied to realize this paradigm, and provide an example showing the solution of the shortest-path problem and demonstrate the healing property of the solution path.

Memcomputing Criteria

While quantum computing relies on the superposition of states, memcomputing utilizes the collective dynamics of a large number of (essentially classical) systems. Its specific criteria are then as follows.

1. Scalable massively-parallel architecture with combined information processing and storage

2. Sufficiently long information storage times

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