Efficient cool down of parallel applications

Abstract—As we move to exascale machines, both peak power and total energy consumption have become prominent major challenges. There has been a lot of research on saving machine energy consumption for HPC data centers. However, a significant part of energy consumption for HPC data centers can be attributed to cooling the machine room. We have already shown significant reduction in cooling energy consumption by constrain-ing core temperatures in our previous work. In this work, we strive to save machine energy consumption while constraining core temperatures in order to provide a total energy solution for HPC data centers that saves both machine and cooling energy consumption. Our approach uses Dynamic Voltage and Frequency Scaling (DVFS) to constrain core temperatures and is particularly designed to reduce the timing penalty associated with DVFS. Using a heuristic that exploits the difference in frequency sensitivity for different parts of an application, we present results that show 17 % reduction in machine energy consumption with as little as 0.9 % increase in execution time while constraining core temperatures below 60 ◦ C. I