The September cover article in the Communications of the Association of Computing Machinery touched off a distinct buzz last month when more than 10 times the usual number of readers downloaded the article in the first two days it went online.

The subject? A survey of progress being made (not much, apparently) in solving the grand challenge for the fields of theoretical computer science and complexity theory. The problem is described rather opaquely as P vs. NP, and it has to do with real world tasks like optimizing the layout of transistors on a computer chip or cracking computer codes.

Like earlier grand math challenges like Fermat’s last theorem, there is a lot at stake, not the least of which is a $1 million cash prize that was offered for the solution as one of seven Mount Everest-style “Millennium Problems” the Clay Mathematics Institute offered almost a decade ago.

So far no one appears to be close to picking up a check. The challenge, in its simplest, but not most understandable phrasing, is to determine whether or not P equals NP. P stands for the class of problems that can be solved in polynomial time, or reasonably quickly. NP stands for the class of problems that can be verified in polynomial time  quickly. If it can be shown that P=NP, then it is possible that the world will be a very different place.