Threshold acceptance algorithm based energy tuning of scientific applications using EnergyAnalyzer

Energy tuning of scientific applications is emerging as an important research agenda among HPC application developer and performance analysis tool developer communities as it is a critical and ponderous task to deal with, especially when exa-scale computing machines were concerned. The energy tuning research has deepened its thrust among researchers due to the necessity of addressing an energy consumption issue of applications which is considered as one of the global challenge. Although a few efforts were carried out in the direction of automatic energy tuning of scientific applications, the working researchers encounter challenges, such as, finding an optimal solution within a short time frame among a wide set of optimization search space, generating fully automatic optimized versions of scientific applications, considering the heterogeneous nature of future generation compute machine architectures, and so forth. This paper discusses about an online based energy consumption tuning mechanism of EnergyAnalyzer tool using Threshold Acceptance (TA) algorithm. In addition, the paper demonstrates the speedy process of finding a near-optimal optimized code versions of a scientific application among a huge set of optimization search space using EnergyAnalyzer. EnergyAnalyzer is an online-based energy consumption analysis tool which is under development at the HPCCLoud Research laboratory of our premise. The proposed algorithm and the energy tuning mechanism could be of an interest to energy conscious scientific application developers and tool developers.