Abstract
With the need to perform data updates on database systems that are increasing in size, researchers are looking for ways to evaluate join queries efficiently under frequent changes to the database. Recently, Idris et al. presented the Dynamic Yannakakis algorithm as one method to solve this problem. In this thesis, a GPU-based implementation of the algorithm is presented, which uses parallelism to further speed up the process. The experimental results comparing the performance of the sequential version and the parallel version of the algorithm are also provided. It is shown that a significant speedup can be obtained by using parallelism, and the speedup increases as the input size grows larger.