Memristors and the Future of Computing

Dhruv Ilesh Shah bio photo By Dhruv Ilesh Shah Comment

Welcome the days of a new kind of electronic device.. All hail the memristor, a device that could revolutionarise the world of computing by implementing wonderful technology!

In 1965, Gordon Moore predicted that the number of transistors in a dense integrated circuit doubles approximately every two years, and since then every manufacturer has been fighting hard to keep up with the Moore’s Law. With the scale of transistor entering sub-20nm, this number is saturating and Moore’s Law has begun to fail us. So what have the scientists and researchers got us? Behold the Memristor (a portmanteau of the words memory and resistor)!

The original concept for memristors, as conceived in 1971 by Professor Leon Chua at the University of California, Berkeley, was a passive, non-linear, two-terminal electrical component that linked electric charge and magnetic flux. Since then, the definition of memristor has been broadened to include any form of non-volatile memory that is based on resistance switching, which increases the flow of current in one direction and decreases the flow of current in the opposite direction and has since then been thought of as the fourth fundamental electrical component.

Memristors constitute a special type of memory, called the ReRAM or resistive RAM, which works by altering the resistance across a dielectric. The outlook of memristors as memory devices started in 1996, when Stanley Williams, the founding director of the Quantum Science Research Laboratory at Hewlett-Packard, began to look for memory devices that are defect intolerant at the nano scale. And what better way to make a device defect-intolerant than too employ the defects themselves for the job!

How Memristors Work : Instead of electrons, memristors use ions as the means of storing information. As the current passes, the holes and defects enable ions of informations to pass through with much greater speed and efficiency - way beyond 1 and 0, to 2, 3 and so on. These levels can be treated as distinct and the demarcation be carried out with ease.

What Does This Mean? At a lower power consumption than a transistor, a memristor can have multiple levels of representing data (upto 6 levels have been achieved), thus reducing the number of memristors required to perform the same task and who knows - the computer may actually become equipped with base-10 memory soon enough! For example, the largest unsigned binary 64-bit ­integer—18,446,744,073,709,551,615—could be held in 20 bits instead of 64. This not only reduces the number of transistors used, but also the complexity of circuits and ease of NLP.

A memristor is often compared to an imaginary pipe that carries water. When the water flows in one direction, the pipe’s diameter expands and allows the water to flow faster – but when the water flows in the opposite direction, the pipe’s diameter contracts and slows the water’s flow down. If the water is shut off, the pipe retains its diameter until the water is turned back on. To continue the analogy, when a memristor’s power is shut off, the memristor retains its resistance value. This would mean that if power to a computer was cut off with a hard shut down, all the applications and documents that were open before the shut down would still be right there the screen when the computer was restarted. Isn’t that cool? Although we have been able to cut down the leakage current in conventional transistors, we cannot dare imagine making them as efficient as a prototype of a memristor! This would mean a big revolution in computing, and the best part is that it could be market-ready much before Quantum Computers (which use qubits to store more data-per-bit).

To see how the non-volatile nature and resistive-switching is achieved, check out this video by Stanley Williams: The 6 Minute Memristor Guide

In fact Hewlett-Packard has a whole unit devoted to developing ‘The Machine’, using electrons for processing, photons for communication, and ions for storage, expected to be completed by 2020.

Jennifer Rupp, a Professor of electrochemical materials at ETH Zurich,is working with IBM to build a memristor-based machine. Memristors, she points out, function in a way that is similar to a human brain: “Unlike a transistor, which is based on binary codes, a memristor can have multi-levels. You could have several states, let’s say zero, one half, one quarter, one third, and so on, and that gives us a very powerful new perspective on how our computers may develop in the future,” she says.

Such a shift in computing methodology would allow us to create “smart” computers that operate in a way reminiscent of the synapses in our brains. Free from the limitations of the 0s and 1s, these more powerful computers would be able to learn and make decisions, ultimately getting us one step closer to creating human-like artificial intelligence.

The outcome of this revolution would only be evident by the next decade, but the fact that nano-electronics has enabled us to revolutionarise the micro-electronics industry is a clear signal - to cope up with our growing computing needs, to explore the vastness of Universe, the path goes from within the Nano World! Memristors and Qubits are all set to power the upcoming generations in unfolding the mysteries of our creation, existence and the universe (multiple of them, in fact!)

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