Early experiences on accelerating Dijkstra's algorithm using transactional memory

In this paper we use Dijkstra's algorithm as a challenging, hard to parallelize paradigm to test the efficacy of several parallelization techniques in a multicore architecture. We consider the application of transactional memory (TM) as a means of concurrent accesses to shared data and compare its performance with straightforward parallel versions of the algorithm based on traditional synchronization primitives. To increase the granularity of parallelism and avoid excessive synchronization, we combine TM with helper threading (HT). Our simulation results demonstrate that the straightforward parallelization of Dijkstra's algorithm with traditional locks and barriers has, as expected, disappointing performance. On the other hand, TM by itself is able to provide some performance improvement in several cases, while the version based on TM and HT exhibits a significant performance improvement that can reach up to a speedup of 1.46.