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March 12, 2008

Promising new approach to molecular computing


The image demonstrates the design of an artificial brain built using a nano-brain reported in this issue of PNAS. Several molecular nano-brain are arranged in a way to work as powerful as our central nervous system. Numerical digits and alphabets float across the architecture demonstrating a matrix generated during a real-time operation similar to the Hollywood blockbuster The Matrix. Credit: Arindam Bandyopadhyay

A powerful new molecular computing device and architecture is making progress. Hat tip: Center for Responsible nanotechnology This looks like a promising approach to radically more powerful computers and a possible pathway to very interesting and powerful molecular devices, machines and factories. The researchers are predicting within 18 months to have 1024 machines working together. They may also be working with Nanoink (maker of dip lithography arrays) for the input and output to the devices. A 2 inch sphere of the devices would equal the computing power of the human brain.

The device can simultaneously carry out 16 times more operations than a normal computer transistor. Researchers suggest the invention might eventually prove able to perform roughly 1,000 times more operations than a transistor.

This machine could not only serve as the foundation of a powerful computer, but also serve as the controlling element of complex gadgets such as microscopic doctors or factories, scientists added.

The device is made of a compound known as duroquinone. This molecule resembles a hexagonal plate with four cones linked to it, "like a small car," explained researcher Anirban Bandyopadhyay, an artificial intelligence and molecular electronics scientist at the National Institute for Materials Science at Tsukuba in Japan.





Bandyopadhyay and his colleagues revealed they could hook up eight other such "molecular machines" to their invention, working together as if they were part of a miniature factory.

Bandyopadhyay added they could expand their device from a two-dimensional ring of 16 duroquinones around the center to a three-dimensional sphere of 1,024 duroquinones. This means it could perform 1,024 instructions at once, for 4**1024 different outcomes — a number larger than a 1 with 1,000 zeroes after it. They would control the molecule at the center of the sphere by manipulating "handles" sticking out from the core.

"We are definitely going to 3-D from 2-D immediately," Bandyopadhyay said.


FURTHER READING
The abstract of the paper: A 16-bit parallel processing in a molecular assembly
A machine assembly consisting of 17 identical molecules of 2,3,5,6-tetramethyl-1–4-benzoquinone (DRQ) executes 16 instructions at a time. A single DRQ is positioned at the center of a circular ring formed by 16 other DRQs, controlling their operation in parallel through hydrogen-bond channels. Each molecule is a logic machine and generates four instructions by rotating its alkyl groups. A single instruction executed by a scanning tunneling microscope tip on the central molecule can change decisions of 16 machines simultaneously, in four billion (4**16) ways. This parallel communication represents a significant conceptual advance relative to today's fastest processors, which execute only one instruction at a time.


[multilevel logic | parallel communication | self-assembly]


researchers in Japan say they have taken a big step toward that nano goal by creating the first molecular machine that can do parallel processing.

Using electrical pulses from the tip of a scanning tunneling microscope, the researchers could flip the control molecule to any one of four configurations, or states. Those flips, in turn, could change the states of the other 16 molecules - just as, say, knocking down one domino can simultaneously set off several chains of falling dominoes.

Mark Ratner, a chemist at Northwestern University who specializes in nanotechnology, said the newly published research represented a significant step toward molecular-scale computers as well as molecular-scale medicine. "People have been talking about both these things for a long time," Ratner told me. "People have even thought about putting these two things together. ... But this is quite pretty because [the researchers] actually use all of the constituents, and that's really neat."

"Is it useful tomorrow? No," he said.

One of the biggest conceptual hurdles has to do with the input/output device: Although the assemblies themselves are at the molecular scale, the scanning tunneling microscope is a big piece of equipment. It wouldn't be practical to use those microscopes to read out the result of a nanocomputer, or harvest the chemicals produced by nanofactories.

Bandyopadhyay said other control methods would be developed for working devices - perhaps optical readers for the nanocomputers, or chemical triggers for the medical nanochips. Ratner said several companies, including an outfit called NanoInk, were working on technologies that might work. [Nanoink created the the dip pen lithography arrays (tens of thousands and million AFMs working in parallel.]

In the meantime, Bandyopadhyay is working to ramp up his molecular machines from two-dimensional arrays to three-dimensional structures. "Within one and a half years we will have 1,024 machines connected," he told me.

Theoretically, the technology could allow for the development of a super-duper information processor contained in a sphere less than 2 inches in diameter, Bandyopadhyay said.

"That will contain the equal amount of components and connectivity that is required inside our brain," he told me.


Physorg also has coverage.

There is a lot of other coverage from the BBC news, fox news and others

Chemistry world has coverage

For Bandyopadhyay, this is just a starting point for building up to more complex assemblies of quinone molecules. 'Now the architecture is like a disk on a surface; I will build a spherical one and realize similar "one to many" communication on that structure's surface,' he says.

However, computation experts contacted by Chemistry World are not yet convinced that this is the way forward. It is not clear, one expert said, whether this system can actually perform parallel computation, or whether it only acts as a hub that distributes a signal. Without a clear demonstration of parallel computation, the work is 'clearly clever, but probably unimportant,' he said.


I think there are challenges ahead but it looks like it can be adapted to a parallel 3d architecture that does computation.

The Telegraph: A molecular machine has been devised as the potential brain of "nanobots" now under study for uses in medicine.


An image imagining an array of the devices


3 comments:

Sigma said...

Got to love competition. They always belittle even the greatest breakthroughs. To me this seems like a HUGE step in the right direction. I mean if we have the computational power of the brain in only a few years... I don't see the singularity being that far away. Very near indeed.

Anonymous said...

Hello Brian,

I was wondering how this would compare to the speed increases of a quantum computer. Would it be equal to QC's speed without the problem of decoherence and only having certain algorithems that are faster than a normal computer?

Thanks,
John Akers

bw said...

Quantum computers can handle different kinds of algorithms. so for certain kinds of problems quantum computers would be superior to a molecular classical computer. A molecular classical computer like this would be could be a million times faster than the best petaflop machines that we have now. Estimates for the human brain are 100 teraflop to 20 petaflops.

http://vadim.oversigma.com/MAS862/Project.html

A large quantum computer with millions of qubits or more would be able to process certain problems faster.
If the qubits could allow say a problem to be solved as the square root of n * n where is the qubits versus the best classical algorithm which might be some exponential function or X**3 or something. then you could see when X**0.333 (where X is the flops of the molecular computer, change the functions based on the kind of problem) is less than n qubits.

This is the same answer that I provided for you at the CRN site just now.
Quantum algorithm versus classical need to be compared.

also some of the dwave systems might only be quantum annealing which might cap out million to a billion times faster than classical. So enough brute force from a molecular computer could whittle down where it would make sense to use a quantum computer. There is also the issue of making the molecular computer easy to program and use. Computing is a tough space because tweaking how we work with CMOS technology could get us to exaflop speeds. Plus the possibility of all optical computers could also be easier than molecular computers. However, the molecular computer would stand out with form factors that the other computers could not match. Putting a lot of really tiny computing and control where you need it like in nanobots.