Congratulations to Eric Anger on successfully defending his PhD proposal “Application-level Modeling and Analysis of Time and Energy for Optimizing Power-constrained Extreme-scale Applications”

The objective of the proposed research is to create a methodology for the modeling and characterization of extreme-scale applications operating within power limitations in order to guide optimization. It is likely that forthcoming high-performance machines will operate with stringent power caps, tying the performance of the systems to their energy-efficiency. Optimizing extreme-scale applications to operate within power limitations will require new techniques for understanding the relationships between application characterization, performance, and energy. The main contributions of this work are: 1) a methodology for the time and energy modeling of high-performance computing applications that can scale to a large number of nodes, 2) characterization of the different ways time and energy are affected by degree of parallelism and processor clock frequency, and 3) optimization of performance under a power cap when scheduling applications, both bulk-synchronous and data-parallel task-based application models.