Heuristic search in PARLOG using replicated worker style parallelism

Most concurrent logic programming languages hide the distribution of processes among physical processors from the programmer. For parallel applications based on heuristic search, however, it is important for the programmer to accurately control this distribution. With such applications, an inferior distribution strategy easily leads to enormous search overheads, thus decreasing speedup on parallel hardware. To solve this problem, various language extensions for concurrent logic languages have been proposed, such as mapping notations and priorities. We present an alternative approach that does not require any new language features. Our solution is to use the replicated workers paradigm in a concurrent logic language (PARLOG). This paradigm has thus far mainly been used in parallel procedural languages, such as Linda and Orca. We show that it is just as useful for logic languages. We have implemented two parallel applications, the Traveling Salesman Problem and alpha-beta search, using this approach. Also, we have done some performance measurements of these programs on a multiprocessor. These experiments show that significant speedups can be obtained in this way.