DNA computations can have global memory

Ever since Adleman's seminal paper (1994) there has been a flood of ideas on how one could use DNA to compute. There have been many papers on using DNA to solve various computational problems. At the top-most level all these papers use DNA in the same way. Each strand of DNA encodes the state of a processor. Each processor operates independently: there is no communication from one processor to another. Processors each search their own part of a large space. The papers differ in the details of how they encode the state into the DNA. They all, however, perform independent searches. Our new result is that we can allow, for the first time, global memory. That is, we show that the individual DNA strands can communication with each other. This changes everything. The point is that DNA can do much more general parallel computations than previously realized. The class of computations that allow global memory are much more powerful than independent searches. For example, one of the main ways to search large spaces is the so called "branch-and-bound" method. In this method the search in one part of the space is "pruned" by values found in other parts of the space. Previously, it was not possible to even imagine how DNA computations could do this: now we know how. Our method is based on the same bio-technology operations that we have used previously. We use no new bio-operations. Thus, our addition of global memory to DNA computations has all the promise and difficulties that previous DNA computations had. The key is that we use nothing new: we just exploit the power of the existing methods in a new way.