Supercomputers can process information about 100 million times faster than a PC, but to power and cool the massive system can also cost millions of dollars.
Researchers are working on an energy efficient biological supercomputer, which they hope ‘will change the way supercomputers are built’.
The team replaced electrons in a chip with a substance that gives human cells energy with the hopes of cutting costs and keeping the system from overheating.
‘The computer consists of a specifically designed, nanostructured network explored by a large number of molecular-motor-driven, protein filaments,’ researchers from McGill University included in the study published in the Proceedings of the National Academy of Sciences.
‘This system is highly energy efficient, thus avoiding the heating issues limiting electronic computers.’
The team used Adenosine triphosphate (ATP) as the power source for the advanced computers and the model created is much smaller, uses less energy, as it uses proteins present in all living cells to function, reports McGill University in a recent press release.
‘We’ve managed to create a very complex network in a very small area,’ said Dan Nicolau, Sr.
‘This started as a back of an envelope idea, after too much rum I think, with drawings of what looked like small worms exploring mazes.’
This new concept birthed from ‘a combination of geometrical modelling and engineering knowhow (on the nanoscale)’.
This is this first step in showing the capabilities of biological supercomputers and how they will perform.
The circuit looks similar to a busy, but very organized, city with roads as seen from an airplane.
Just like in a city, cars and trucks of different shapes and sizes, powered by different types of motors are zipping around the roads—consuming the fuel they need to keep moving.
In the case of this study, the city is a chip about 1.5 cm square in which the ‘roads’ have been etched into.
Researchers replaced the traditional electrons that are propelled by an electrical charge, with ‘shoe strings’ of proteins that travel around the chip in a controlled fashion powered by ATP.
All these features will keep the system from becoming too hot and keep energy use down to a minimum.
‘We implemented the proposed computational approach with biological agents that satisfy the following requirements: The agents (proteins) are available in large numbers at negligible cost; are self-propelled and thus do not require a global, external driving force; operate independently of each other to ensure parallel exploration; have small dimensions to enable use in high-density networks with high computing power per unit area; move rapidly to maximize computational speed; and move in a predominantly forward direction (to ensure low error rates),’ according to the study.
‘Now that this model exists as a way of successfully dealing with a single problem, there are going to be many others who will follow up and try to push it further, using different biological agents, for example,’ said Nicolau.
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