  The upcoming exascale era will push the changes in computing architecture
from classical CPU-based systems in hybrid GPU-heavy systems with much higher
levels of complexity. While such clusters are expected to improve the
performance of certain optimized HPC applications, it will also increase the
difficulties for those users who have yet to adapt their codes or are starting
from scratch with new programming paradigms. Since there are still no
comprehensive automatic assistance mechanisms to enhance application
performance on such systems, we are proposing a support framework for future
HPC architectures, called EASEY (Enable exASclae for EverYone). The solution
builds on a layered software architecture, which offers different mechanisms on
each layer for different tasks of tuning. This enables users to adjust the
parameters on each of the layers, thereby enhancing specific characteristics of
their codes. We introduce the framework with a Charliecloud-based solution,
showcasing the LULESH benchmark on the upper layers of our framework. Our
approach can automatically deploy optimized container computations with
negligible overhead and at the same time reduce the time a scientist needs to
spent on manual job submission configurations.
