Improving MPI applications performance on multicore clusters with rank reordering
EuroMPI'11 Proceedings of the 18th European MPI Users' Group conference on Recent advances in the message passing interface
Network-theoretic classification of parallel computation patterns
International Journal of High Performance Computing Applications
Multiclass classification of distributed memory parallel computations
Pattern Recognition Letters
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Interprocessor communication is an important factor in determining the performance scalability of parallel systems. The communication requirements of a parallel application can be quantified to understand its communication pattern and communication pattern similarities among applications can be determined. This is essential for the efficient mapping of applications on parallel systems and leads to better interprocessor communication implementation among others. This paper proposes a methodology to compare the communication pattern of distributed-memory programs. Communication correlation coefficient quantifies the degree of similarity between two applications based on the communication metrics selected to characterize the applications. To capture the network topology requirements, we extract the communication graph of each applications and quantities this similarity. We apply this methodology to four applications in the NAS parallel benchmark suite and evaluate the communication patterns by studying the effects of varying problem size and the number of logical processes (LPs).