Effect of MPI tasks location on cluster throughput using NAS

Abstract

In this work the Numerical Aerodynamic Simulation (NAS) benchmarks have been executed in a systematic way on two clusters of rather different architectures and CPUs, to identify dependencies between MPI tasks mapping and the speedup or resource occupation. To this respect, series of experiments with the NAS kernels have been designed to take into account the context complexity when running scientific applications on HPC environments (CPU, I/O or memory-bound, execution time, degree of parallelism, dedicated computational resources, strong- and weak-scaling behaviour, to cite some). This context includes scheduling decisions, which have a great influence on the performance of the applications, making difficult to achieve an optimal exploitation with cost-effective strategies of the HPC resources. An analysis on how task grouping strategies under various cluster setups drive the execution time of jobs and the infrastructure throughput is provided. As a result, criteria for cluster setup arise linked to maximize performance of individual jobs, total cluster throughput or achieving better scheduling. To this respect, a criterion for execution decisions is suggested. This work is expected to be of interest on the design of scheduling policies and useful to HPC administrators.