Researchers Use Genetic Algorithms To Push Past the Limits of Moore's Law

Genetic Algorithms  

Scientists have demonstrated working electronic circuits that have been 'designed' in a radically new way, using methods that resemble Darwinian evolution. The size of these circuits is comparable to the size of their conventional counterparts, but they are much closer in operation to natural networks like our brain.

Scientists of the MESA+ Institute for Nanotechnology and the CTIT Institute for ICT Research at the University of Twente in The Netherlands have demonstrated working electronic circuits that have been produced in a novel way, using methods that resemble Darwinian evolution. The size of these circuits is comparable to the size of their conventional counterparts, but they are much closer to natural networks like the human brain.

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The findings promise a new generation of powerful, energy-efficient electronics, and have been published in the journal Nature Nanotechnology.

During the last few years computers have become more and more powerful by integrating ever smaller components on silicon chips, in the familiar pattern of Moore's Law. The technology has reached a point where it is becoming increasingly difficult and extremely expensive to continue this miniaturization. 

Current transistors consist of only a handful of atoms. It is a major challenge to produce chips in which the millions of transistors have the same characteristics, and thus to make the chips operate without error. Another drawback is that their energy consumption is reaching unacceptable levels. It is obvious that one has to look for alternative directions, and it is interesting to see what we can learn from nature. Natural evolution has led to powerful ‘computers’ like the human brain, which can solve complex problems in an energy-efficient way. Nature exploits complex networks that can execute many tasks in parallel.

The approach of the researchers at the University of Twente is based on methods that resemble those found in nature. They have used networks of gold nanoparticles for the execution of essential computational tasks. Also, unlike conventional electronics, they have moved away from designed circuits. 

Using 'designless' systems, costly design mistakes are avoided. The computational power of their networks is enabled by applying artificial evolution, also known as genetic algorithms. This evolution takes less than an hour, rather than millions of years. By applying electrical signals, one and the same network can be configured into 16 different logical gates. The evolutionary approach works around - or can even take advantage of - possible material defects that can be fatal in conventional electronics.

It is the first time that scientists have succeeded in this way in realizing robust electronics with dimensions that can compete with commercial technology. 

"With this research we have delivered proof of principle: demonstrated that our approach works in practice."

According to lead researcher Wilfred van der Wiel, the circuits currently generated with the artificial evolution method still have limited computing power. “But with this research we have delivered proof of principle: demonstrated that our approach works in practice. By scaling up the system, real added value will be produced in the future. Take for example the efforts to recognize patterns, such as with face recognition. This is very difficult for a regular computer, while humans and possibly also our circuits can do this much better." 

Another key advantage may be that this type of circuitry uses much less energy, both in the production, and during use. The researchers anticipate a wide range of applications, in portable electronics and in the medical field.

SOURCE  University of Twente

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