Detail map of San Diego, California, United States,Columbia, South Carolina, United States

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Massimiliano Di Ventra and Yuriy Pershin Outline Memcomputing

11/19/2012
Symbols of the three memory elements that the authors consider for memcomputing. Memcapacitive (left), memristive (center), and meminductive (right) systems.

Symbols of the three memory elements that the authors consider for memcomputing. Memcapacitive (left), memristive (center), and meminductive (right) systems.

On November 19, 2012 physicists Massimiliano Di Ventra at the University of California, San Diego and Yuriy Pershin at the University of South Carolina, Columbia, outlined an emerging form of computation called memcomputing based on the discovery of nanoscale electronic components that simultaneously store and process information, much like the human brain.

At the heart of this new form of computing are nanodevices called the memristor, memcapacitor and meminductor, fundamental electronic components that store information while respectively operating as resistors, capacitors and inductors. These devices were predicted theoretically in the 1970s but first manufactured in 2008. Because these devices consume very little energy computers using them could approach the energy efficiency of natural systems such as the human brain for the first time.  

"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. . . ." (Di Ventra & Pershin, "Memcomputing: a computing paradigm to store and process information on the same physical platform," http://arxiv.org/pdf/1211.4487v1.pdf, accessed 11-22-2012). 

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