Scalable performance bounding under multiple constrained renewable resources

In the age of exascale computing, it is crucial to provide the best possible performance under power constraints. A major part of this optimization is managing power and bandwidth intelligently in a cluster to maximize performance. There are significant improvements in the power efficiency of HPC runtimes, yet little work has explored our ability to determine the theoretical optimal performance under a give power and bandwidth bound. In this paper, we present a scalable model to identify the optimal power and bandwidth distribution such that the makespan of a program is minimized. We utilize the network flow formulation in constructing a linear program that is efficient to solve. We demonstrate the applicability of the model to MPI programs and provide synthetic benchmarks on the performance of the model.