TY - JOUR
T1 - Energy analysis of code regions of HPC applications using EnergyAnalyzer tool
AU - Benedict, Shajulin
AU - Rejitha, R. S.
AU - Preethi, C.
AU - Bright, C. Bency
AU - Judyfer, W. S.
N1 - Publisher Copyright:
Copyright © 2017 Inderscience Enterprises Ltd.
PY - 2017
Y1 - 2017
N2 - Energy consumption analysis is emerging as a crucial step for analysing scientific applications. It is essential for application developers to design energy-conscious parallel algorithms. Even though there exist some power measuring tools for parallel machines, code region specific energy consumption analysis tools for scientific applications, especially when the future exa-scale or large-scale computing machines were targeted, are very rare and are challenging to implement. This paper focuses on revealing the design methodology of EnergyAnalyzer tool - a code region-based energy consumption analysis tool for scientific applications. The tool was experimented with several HPC applications, such as, multiple EM for motif elicitation (MEME), gapped local alignment of motifs (GLAM2), high performance computing challenge (HPCC) benchmarks, NAS parallel benchmarks (BT, CG, EP, FT, LU, MG, SP, and so forth), and a few other HPC benchmarks, at our HPCCLoud Research Laboratory. In addition, we investigated the energy consumption of code regions of MEME/GLAM2 applications when the application specific parameters were modified.
AB - Energy consumption analysis is emerging as a crucial step for analysing scientific applications. It is essential for application developers to design energy-conscious parallel algorithms. Even though there exist some power measuring tools for parallel machines, code region specific energy consumption analysis tools for scientific applications, especially when the future exa-scale or large-scale computing machines were targeted, are very rare and are challenging to implement. This paper focuses on revealing the design methodology of EnergyAnalyzer tool - a code region-based energy consumption analysis tool for scientific applications. The tool was experimented with several HPC applications, such as, multiple EM for motif elicitation (MEME), gapped local alignment of motifs (GLAM2), high performance computing challenge (HPCC) benchmarks, NAS parallel benchmarks (BT, CG, EP, FT, LU, MG, SP, and so forth), and a few other HPC benchmarks, at our HPCCLoud Research Laboratory. In addition, we investigated the energy consumption of code regions of MEME/GLAM2 applications when the application specific parameters were modified.
KW - Energy analysis
KW - HPC
KW - Performance analysis
KW - Scientific applications
KW - Tools
UR - http://www.scopus.com/inward/record.url?scp=85019737074&partnerID=8YFLogxK
U2 - 10.1504/IJCSE.2017.084163
DO - 10.1504/IJCSE.2017.084163
M3 - Article
AN - SCOPUS:85019737074
SN - 1742-7185
VL - 14
SP - 267
EP - 278
JO - International Journal of Computational Science and Engineering
JF - International Journal of Computational Science and Engineering
IS - 3
ER -