Abstract:
Dynamic programming on tree decompositions is often a key for solving a widerange
of optimization problems that would otherwise be intractable. Operations on
tree decompositions are amenable to parallelization. However, a systematic approach
towards such parallelization is still lacking. In this work, we present a generic and flexible
framework for parallel dynamic programming on tree decompositions that can be
easily adapted to solve any graph theoretic optimization problem on graphs of bounded
treewidth. We show the effectiveness of our framework using the Dominating Set problem
as a case study. Our experiments show notable speedups compared to the serial
approach.
