On scaling dynamic programming problems with a multithreaded tabling Prolog system

Tabling is a powerful implementation technique that improves the declarativeness and expressiveness of traditional Prolog systems in dealing with recursion and redundant computations. It can be viewed as a natural tool to implement dynamic programming problems, where a general recursive strategy divides a problem in simple sub-problems that are often the same. When tabling is combined with multithreading, we have the best of both worlds, since we can exploit the combination of higher declarative semantics with higher procedural control. However, at the engine level, such combination for dynamic programming problems is very difficult to exploit in order to achieve execution scalability as we increase the number of running threads. In this work, we focus on two well-known dynamic programming problems, the Knapsack and the Longest Common Subsequence problems, and we discuss how we were able to scale their execution by using the multithreaded tabling engine of the Yap Prolog system. To the best of our knowledge, this is the first work showing a Prolog system to be able to scale the execution of multithreaded dynamic programming problems. Our experiments also show that our system can achieve comparable or even better speedup results than other parallel implementations of the same problems.