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Memristor Processor Solves Mazes
Physicists have designed a memristor processor that uses a massively parallel approach to solve mazes.
Memristors are the fourth fundamental building block of electronic circuits, after resistors, capacitors and inductors. They were famously predicted in the early 1970s but only discovered 30 years later at HP Labs in Palo Alto, California.
Memristors are resistors that “remember” the state they were in, which changes according to the current passing through them. They are expected to revolutionise the design and capabilities of electronic circuits and may even make possible brain-like architectures in silicon, since neurons behave like memristors.
Today, we see one of the first revolutionary circuits thanks to Yuriy Pershin at the University of South Carolina and Massimiliano Di Ventra at the University of California, San Diego, two pioneers in this field. Their design is a memristor processor that solves mazes and it is remarkably simple.
Mazes are a class of graphical puzzles in which, given an entrance point, one has to find the exit via an intricate succession of paths, with the majority leading to a dead end, and only one, or few, correctly “solving” the puzzle.
Pershin and Di Ventra begin by creating a kind of a universal maze in the form of a grid of memristors, in other words an array in which each node is connected to another by a memristor and a switch. This can be made to represent any regular maze by switching off certain connections within the array.
Solving this maze is then simple. Simply connect a voltage across the start and finish of the maze and wait. “The current flows only along those memristors that connect the entrance and exit points,” say Pershin and Di Ventra. This changes the state of those memristors allowing them to be easily identified. The chain of these memristors is then the solution.
That’s potentially much quicker than other maze solving strategies which effectively work in series. “The maze is solved in a massively parallel way, since all memristors in the network participate simultaneously in the calculation,” they say.
They’ve tested the idea with a memristor simulator, a computer program that reproduces the behaviour of real memristors, and say it works well. And implementing the device in silicon will become easier as more development work is done in this area.
Of course, it’s not just the memristors that are doing the calculating here. Their network structure and layout is crucial too. When a maze is created, the answer is already embedded in its structure, well before any computation begins. The only question is how easily it can be extracted. This new approach, in which the entire structure of maze takes part, is clearly powerful.
That makes Pershin and Di Ventra’s work part of a growing body of interest in the role that form and structure play in processing information. If you’re in any doubt the significance of this so-called morphological computing, think about how the human body walks or jumps.
There is increasing evidence that the brain has much less involvement with this kind of movement than anybody imagined. Instead, the shape, form and material properties of bones, ligaments and muscles largely control the detail of what happens. In effect, the brain outsources control to the morphology of the system.
This kind of memristive processing falls into a similar category. Expect to hear more about it.
Ref: arxiv.org/abs/1103.0021: Solving Mazes With Memristors: A Massively-Parallel Approach
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