IDEA FRIDAY: Memristor-The Fourth Element of a Circuit
If you are a Physics freak such as I am, then you will probably appreciate this neat piece of innovation that is being applied in exquisite ways, which by effect will transport us into that techno-idyllic future we so constantly pursue-the very stuff of a Vernian literary exposé. What I describe as a TECHNOTOPIA ( utopic renditions brought about by technological evolution to such a manner that it guarantees our very survival, well, that’s one way to put it; but it always gets complicated between humans and technology, precisely because it quantum leaps artificial intelligence years ahead, not to mention, my favorite, Brain Science).
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What is the Memristor?
To understand what a memristor is, we first need to be familiar with the properties basic electrical circuits, constructed from three ideal elements, that is, a resistor, capacitor, an inductor, and an ideal voltage source (expressed by the formula v (t); these are standard stuff you learn in your first Physics class. Here is how it goes- an ideal capacitor is defined by the single-valued relationship between and the charge. Akin to that, an ideal resistor is defined by the single-valued relationship between the current and the voltage. Similarly, an ideal inductor is defined by the single valued relationship between the magnetic flux and current; there are formulae to describe these relationships as would all good Mathematics do, but it is Friday, so I’ll spare you.
However, I will say the following-these three definitions provide three relations between the four fundamental constituents of Circuit Theory, namely, the charge q, current i, voltage v, and magnetic flux ?. The definition of current, i=dq/dt, and the Lenz’s law, v=+d?/dt, offer two more relations between the four constituents, leading up to a total of five relations. I did say it was Friday (the 13th, no less, let saner minds forgive me) and there would be no formulae, well, gentle-folk, I may have misappropriated the truth, but only to serve to the edification of your minds such that I plead clemency from you for having to endure a bit of technicality, but a little technicality a day keeps the mental atrophy away, but what do I know, am just a Pied Piping fellow calling you to the tune of knowledge and disappear into the meadows green of understanding.
Let’s resume- five relations you query-let’s see if I can elaborate it further, but in the form of a question; so these five relations that I have above-mentioned conjured a natural query, is there an ideal element that related the charge q (t) and magnetic flux ? (t)? One man answered that question of symmetry, Leon Chua, a professor in the Electrical Engineering and Computer Sciences Department of the University of California at Berkeley; that was forty-four years ago. Chua postulated that a new ideal element defined by the single-valued relationship d?=M (q) dq must exist.
He dubbed the element Memristor, M, which was short for memory resistor. This brilliant hypothesis meant that the trio of ideal circuit elements, RCL, could not provide a model for a rudimentary real-world circuit that would have a memristive component as well. So, in my studies, this fourth element, M, gave birth to the sixth relation that would express the charge and magnetic flux, meaning the ideal circuit would be RCLM. So, what do the letters RCL stand for? Well, Resistor, Capacitor, and Indicator. Basically, a circuit is the relation of those three, until came Memristor M. The reason that the memristor is so different from the other three basic circuit elements is that, unlike them, it retains memory without power. In layman’s terms, this means that if you did a hard shutdown on your computer and then restarted it, all the applications and documents you had open before you shut down would still be right there on your screen when you restarted. That’s an effect that can’t be duplicated by any circuit combination of resistors, capacitors and inductors today, which is why researchers feel the memristor qualifies as a fourth fundamental circuit element. In spite of the simplicity and the soundness of the symmetry argument that predicts the existence of the fourth ideal element, experimental realization of a quasi-ideal memristor—defined by the single-valued relationship d?=M(q)dq—remained as elusive as the obvious.
So, in 2008, scientists at HP Labs built the first working memristor. Nevertheless, no end-devices and models have been presented. Also, new applications appear frequently. However, the integration of the device at the circuit level is not straightforward, because available models are still immature and/or suppose high computational loads, making their simulation long and cumbersome. Nonetheless, the use of a memristor application framework to support the work of both the model developer and the circuit designer is providing a solution. First, the framework includes a library with the best-known memristor models, being easily extensible with upcoming models. Systematic modifications have been applied to these models to provide better convergence and significant simulations speedups. Second, a quick device simulator allows the study of the response of the models under different scenarios, helping the designer with the stimuli and operation time selection. Third, fine tuning of the device including parameters variations and threshold determination is also supported. Finally, SPICE/Spectre subcircuit generation is provided to ease the integration of the devices in application circuits. The framework provides the designer with total control overconvergence, computational load, and the evolution of system variables, overcoming usual problems in the integration of memristive devices.
Some Features of a Memristor
-It can act like a switching transistor by moving the memristor’s resistance to the far right as an “on” and then moving it to the far left as “off”. You can read the resistance by passing a very small amount of current that trivially/does not affect the current state (for instance, use AC current to very slightly change it then change it right back to what it was). Thus you have a passive switch with low current requirements for reading and a bit higher for writing (toggle the switch).
-You can encode more complex state. Don’t just use two parts of the curve (i.e., a switch), use the left right and center to create 3 state logic. You can continue getting more complex, and potentially use many different points on the curve for state (e.g., 256 bits on one memristor).
-They are small. Already on the scale of 10’s of nm. They are very competitive with current transistor fabrication sizes.
-They are passive and non-volatile, meaning they will hold their state longer and with less energy requirements.
-They are easier to scale in 3D. As long as they are isolated by a small barrier you can stack them on top of each other. Since they are passive you do not need any kind of biasing lines, etc. which is an extremely important benefit.
-The way they hold state is very similar to neurons. Memristors don’t have a firing mechanism, but react very similar. If you combine these passive, continuous state devices into large 3D grids you have a whole new platform for creating artificial intelligence on that isn’t available right now. You essentially “imprint” state onto this memristor memory model and by increasing the complexity of the reading/writing; we may get closer to real AI.
How it fundamentally works is just that it is a theoretical component that’s resistance changes proportionally to the amount of charge that has been through it in the past. And so, you can think of memristors in a lot of different ways. Initially, they are a passive device just like passive RLCs. Second, they are essentially variable resistors. Their internal resistance changes by the amount of current passing through it. It follows a hysteresis curve governed by a simple formula which makes it a very predictable device. Since it pursues this well-defined curve, we can use it for memory.
Practical devices approximating a memristor have been developed that could be used as high speed, dense memory devices that would potentially replace RAM and flash.
Applications of the MEMRISTOR
Memristor-based memory is the most BLATANT application of memristors. One memristor can store a single bit of data in a DRAM-like architecture, where the capacitors are replaced with memristors. This kind of memory has many advantages as compared to SRAM and DRAM; it has no leakage power, is non-volatile, and exhibits good scalability. Memristor-based memory is superior to flash memory in terms of speed and scalability. One memristor can even store more than one bit, in an approach similar to multilevel flash memory.
Memristors behave similarly to biological synapses. This characteristic makes memristors good building blocks in neuromorphic systems, where neurons and synapses are modeled as electronic devices. Memristors and neural applications have always been considered a perfect match. The strong affinity between them is generally based upon the assumption that memristors would be used to mimic a complex network of neurons. Unfortunately, this purely analog implementation is impractical given the serious issues that currently remain with the technology, such as low write endurance and high defect rates. We find that a hybrid digital-analog approach is needed. In addition, it has been exploited that memristors’ unique analog properties can be utilized to develop general techniques that can leverage devices with significantly low durability (for example, devices that can survive only a few hours of continuous switching). These new techniques can provide a system lasting for five or more years of continuous operation.
The intended long-term use of this technology is to simulate the brain, as they are expected to provide the form factor of a brain, the low power requirements, and the instantaneous internal communications. Our research referenced below is an initial step towards integrating the memristor technology into challenging environments starting from wireless sensor networks and up to highly updated neural nets such as the brain. This is the whole ideal of the INTERNET OF YOU.
Another possible application of memristors is logic circuits. Memristors can be used in hybrid CMOS-memristor circuits, or as a standalone logic gate. One notable logic application is using memristors in an FPGA, as configurable switches, connecting the CMOS logic gates. A different approach is using memristors as building blocks of the logic gate itself. Since memristors are memory elements, a single memristor can be used as the input, output, or computational logic building block. In this approach, the logic state is represented as resistance, where a high resistance is logical state zero, and a low resistance is logical state one. Here’s to computer nerds!
Leon Chua said: “Since our brains are made of memristors, the flood gate is now open for commercialization of computers that would compute like human brains, which is totally different from the von Neumann architecture underpinning all digital computers.”
Memristor technology and its application focus on what I mentioned at the outset, a TECHNOTOPIC society where there are self-learning neural networks, artificial consciousness, uber-computers on a massive degree, the possibilities are exciting and endless.