Abstract:
We empirically compare a variety of current algorithms used to map scientific computations onto massively parallel computers. The comparison is performed using Chaco, a publicly available graph partitioning code written by the authors. Algorithms are evaluated in terms of both computing cost and quality of partition as judged by execution time of the parallel application.