Energy consumption analysis and energy optimization techniques of HPC applications

Abstract

High Performance Computing ( HPC) is used for running advanced application programs efficiently, reliably, and quickly. HPC makes use of both parallel as well as distributed computing technologies. In earlier decades, performance analysis of HPC applications was evaluated based on speed, scalability of threads, memory hierarchy. Now, it is essential to consider the energy or the power consumed by the system while executing an application. There exist performance analysis tools, such as, Periscope, Scalasca, Vampir, TAU, and Paradyn, which consider hardware based performance bottlenecks and memory hierarchy issues including EnergyAnalyzer which is a dedicated tool for energy analysis purpose.Recently, these tools have focused on doing an automatic tuning of HPC applications which require a wide study of HPC applications in terms of power consumption.This paper aims at experimenting the most commonly used HPC applications and express the HPC application developers or tool developers that power consumption will be higher in certain conditions. We have done the experiments in HPCCLoud Research Laboratory, India.The experimental results were impressive when tested for the energy consumption ofHPC applications.

The Effect of Parallel Programming Languages on the Performance and Energy Consumption of HPC Applications

“…Rejitha et al have analyzed the effect of loop optimization techniques on the use of energy consumed by different techniques [7]. Although they have compared different such techniques but they did not implement them using all available models in HPC www.ijacsa.thesai.org environment.…”