High Performance Computing (HPC) applications are highly complex and demand ecient execution. Energy require-
ment of current petascale and future exascale systems is a major cause for concern, and it is crucial to improve the
energy-eciency of the applications that run on these systems. A signi cant source of improvement for applications is
that they commonly exhibit dynamic resource requirements. Consequently, such dynamism in an application presents
opportunity to tailor the utilisation of resources in the HPC system based (...)

High Performance Computing (HPC) applications are highly complex and demand ecient execution. Energy require-
ment of current petascale and future exascale systems is a major cause for concern, and it is crucial to improve the
energy-eciency of the applications that run on these systems. A signi cant source of improvement for applications is
that they commonly exhibit dynamic resource requirements. Consequently, such dynamism in an application presents
opportunity to tailor the utilisation of resources in the HPC system based on the requirements of the application at
runtime. READEX (Runtime Exploitation of Application Dynamism for Energy-ecient eXascale computing) is a EU
Horizon 2020 FET-HPC project whose objective is to exploit the dynamism found in HPC applications at runtime to
achieve ecient computation on exascale systems. Alya is a high performance computational mechanics application that
is present in the Uni ed European Application Benchmark Suite and the PRACE Accelerator Benchmark Suite. In this
paper, we apply the READEX methodology on Alya to identify and exploit any dynamism that is exhibited. We report
on the potential energy savings and the e ects on the application runtime, where we observe 5-20% reduction in the
energy consumed by the application.