My 10/12/08 Missoulian column
Time is money, they say, and that’s especially true when it’s computer time and you’ve got a huge program – such as software that models and helps predict the weather – that takes hours to run and many people depend on accurate results.
Even when computer time is measured in nanoseconds, if a few minutes can be shaved away from the time it takes a program to run, that’s time that can be given over to more processing, which can be given over to solve more complex problems.
So researchers involved with computer processing technology are constantly pushing the envelope to find ways to speed up information processing, and one idea that is gaining ground is a move away from traditional integrated circuits to some proven but basic concepts that use processors built with DNA. Yes, that DNA – the stuff the makes cells work and holds our genetic information.
Now this doesn’t mean we are going to sprout wires or keyboards and turn into walking computers. We’re talking about DNA computers in the laboratory, computers in test tubes, and none of them is “alive” in a strict sense of the word. DNA is simply the component of “wetware” – a DNA computer – that acts much the same way the integrated circuit logic switches and hardware memory works in your home PC. (And here, I’m using DNA in a generic sense, as I can’t cover all the different aspects of human genetic material).
All DNA computers are still in the early stages, but such processing is promising because of both the speeds that are possible and the size of the logic that performs the processing. Moving from electronic logic gates, which are coming close to the limits of getting smaller, to logic built with DNA, on the molecular level, would be an astounding technological leap.
DNA might be a practical way to go because of Moore’s Law, which states that the number of components on integrated circuits will double about every 18 months. Obviously, with chips, Moore’s Law can’t continue indefinitely, because there is a point at which transistors and other components can’t be made smaller and packed more tightly in a chip. Moore’s Law will hold true for another decade or two, many say, and chips will get denser with logic gates, but after that, it’s a brick wall.
The idea behind using DNA for computers is the same as integrated circuits: the logic gates that do the processing work. Of course, a computer doesn’t care what it is made of, and a typical user doesn’t usually know or care, either, as long as it works. If logic gates and switches made from materials other than silicon chips can work reliably and faster, then progress will go that way. The bottom line is better performance and perfect accuracy.
DNA logic has other advantages over current hardware logic. DNA logic has more “states” than electronic logic. Current hardware logic only works with ones and zeros, while DNA logic can work with four states – such as zero, one, two and three – because DNA strands are made up of four amino acids that can be “switched” on and off. That means much more processing can be done and more sophisticated instructions can be given to DNA logic.
And while electronic computers mostly work in a linear fashion – one job at a time, one decision at a time – DNA can work in parallel, processing lots of streams of data at once. In fact, hugely parallel processing is possible, with millions of simultaneous operations. Which means much more work gets done in the same amount of time because the problem is divided up into those million smaller operations that get done at the same time, even if each step in the DNA processing cycle is slower because the operations are chemical instead of electronic. And DNA is much smaller than anything electronic, so the memory capacity is enormous. Need more memory? Simply grow it.
Some of these concepts have been proven in the lab while some others are still in development. Google “DNA computers” and you’ll get lots of reading material. Working DNA computers are years away, but they have enough promise that research keeps speeding along.
The need for more speed is obvious because more and more complex problems arise every day, problems that can’t possibly be solved without some form of data processing. Research into climate change, for example, requires processing of increasing amounts of data with increasingly sophisticated software based on algorithms that attempt to replicate parts of climate systems for modeling.
Commercial businesses – such as airlines – are always interested in more powerful processing. Airlines and shipping companies are constantly working with what are called “traveling salesman” problems. The best route for a traveling salesman is one that allows him to visit each of his cities with the least amount of backtracking. That same best solution will also have the least amount of total mileage while stopping often enough at all of his cities. It seems easy to figure out, but with more than five or six cities to visit, a traveling salesman problem gets complex very quickly, with millions of possible trip routes in the most complex cases.
Any computer is happy – well, happy doesn’t calculate into the equation – to do the same things over and over again. In fact, they just don’t care. So they can take a traveling salesmen problem and chew on it for hours and days, and the faster they are, the more complex problems can be solved, and faster. Modeling climate, determining efficient traveling routes, investigating diseases and treatments, anything that can be summed up in an algorithm and then implemented in software can benefit.
Another idea behind DNA computers is the possibility to be able to have them do work inside a living cell: diagnose cancer, repair cells and more. Using DNA to repair DNA might be possible. But few will speculate when those treatments might be available in the local hospital.
But if computer technology can move away from electronics and silicon chips and hardware can be made with DNA for a great increase in speed and a great decrease in size, then all the better for solving complex problems. The world runs on data processing, and that’s not going to change.