Performance and Power Characteristics and Optimizations of Hybrid MPI/OpenMP LULESH Miniapps under Various Workloads

Abstract

Energy efficient execution of scientific applications requires insight into how HPC system features affect the performance and power of the applications. In this paper, we analyze and model performance and power characteristics of hybrid MPI/OpenMP LULESH (Livermore Unstructured Lagrange Explicit Shock Hydrodynamics) miniapps under various workloads using MuMMI (Multiple Metrics Modeling Infrastructure). Output from these models is then used to guide code optimizations of performance and power. Our optimization methods result in performance improvement and energy savings of up to approximately 10%. Further, based on the insight learned from our models and measurements under various workloads, applying DCT (Dynamic Concurrency Throttling) to the optimized codes results in the energy savings by 43.12% to 58.30% for different problem sizes compared with the baseline results on 27 nodes with 32 threads per node on a 36-node Intel Haswell testbed cluster Shepard.