Franz-Christian Heinrich - Modeling, Prediction and Optimization of Energy Consumption of MPI Applications using SimGrid

The High-Performance Computing (HPC) community is currently undergoing disruptive technology changes in almost all fields, including a switch towards massive parallelism with several thousand compute cores on a single GPU or accelerator and new, complex networks.

The energy consumption of these machines will continue to grow in the future, making energy one of the principal cost factors of machine ownership. This explains why even the classic metric "flop/s", generally used to evaluate HPC applications and machines, is widely regarded as to be replaced by an energy-centric metric "flop/watt". 

One approach to predict energy consumption is through simulation, however, an accurate simulation of the system is crucial to estimate the energy faithfully. In this thesis, we contribute to the performance and energy prediction of HPC architectures. We propose an energy model which we have implemented in the open source SimGrid simulator. We validate this model by carefully and systematically comparing it with real experiments.  We leverage this contribution to both evaluate existing and propose new DVFS governors that are particularly designed to suit the HPC context.