Energy and Performance Analysis of Parallel Particle Solvers from the ScaFaCoS Library

Performance analysis in high performance computing (HPC) has traditionally focused on improving application programs, for example, by decreasing the overall runtime or increasing the throughput of floating point operations. However, the same approaches might also be used to influence the energy behavior. Since the increasing energy consumption of HPC platforms is gaining more and more attention, the identification of applications and platforms for which energy and performance measurement lead to differing results is of great importance. In this article, we analyze the energy and performance behavior of particle solvers from the ScaFaCoS library. Four different criteria are investigated with respect to their influence on the energy consumption and achieved performance. These criteria are the solution method chosen, the parameters of the solution method, the degree of parallelism, and the parameters of the hardware platform.