Undoubtedly, the processing power of ideal computers will reach its peak in next 10-25 years. Even on this apex, the customary computer systems wouldn’t be able to take care of specific problems including combination of variables that come with multiple possible solutions, ad then find the best solution among those. Recently, a new kind of computer was reported that has ability to blend electrical and optical processing. This computer will be able to take care of impending processing barrier and get answers for the problems. If this is scaled up, the new computer can save lot of costs by sorting a few more optimal solutions of problems that have high number of possible solutions.
Peter McMohan, a postdoctoral scholar in applied physics says, “This is a machine that’s in a sense the first in its class, and the idea is that it opens up a sub-field of research in the area of non-traditional computing machines. There are many, many questions that this development raises and we expect that over the next few years, several groups are going to be investigating this class of machine and looking into how this approach will pan out.” There is a specific kind of problem known as combinatorial optimization problem, the traditional computers are unable to solve it. The best example of what’s known as “traveling salesman” problem – under this problem a salesman need to visit particular set of cities just once and come back to the first city. The salesman needs to take the most efficient possible route.
The problem may seem a simple one from surface, there are multiple possible routes that multiplies in size as the number of cities increases. This increases the complexity of problem. Alireza Marandi, a previous postdoctoral scholar at Stanford says, “Those problems are challenging for standard computers, even supercomputers, because as the size grows, at some point, it takes the age of the universe to search through all the possible solutions. This is true even with a supercomputer because the growth in possibilities is so fast.”
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