Mesh partitioning is an important step for parallel scientific applications, in particular finite element analyses. A good partitioner will minimize both the time spent on local computation and on interprocessor communication. It is often the case that these two goals cannot be satisfied simultaneously. In this paper, we use analytical and experimental results to illustrate the importance of considering the target architecture as well as the application when determining which factor to emphasize in a partitioning method. In particular, we derive a parameter η0 that provides some guidelines as to which goal should be given primary focus. Our results yield two interesting facts: (1) allowing some load imbalance can provide some reduction in communication and total execution times and (2) as larger numbers of processors are applied to a problem, larger amounts of load imbalance are beneficial.
ASJC Scopus subject areas
- Theoretical Computer Science
- Hardware and Architecture
- Computer Networks and Communications
- Artificial Intelligence