Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1504/IJCSE.2017.10005024 | IJCSE |
Keywords | Field | DocType |
energy analysis, HPC, performance analysis, scientific applications, tools | Computer architecture,Supercomputer,Parallel algorithm,Computer science,Design methods,Real-time computing,Computational science,Smith–Waterman algorithm,HPC Challenge Benchmark,Energy consumption,Code (cryptography),Multiple EM for Motif Elicitation | Journal |
Volume | Issue | ISSN |
14 | 3 | 1742-7185 |
Citations | PageRank | References |
0 | 0.34 | 16 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| shajulin benedict | 1 | 69 | 13.68 |
| Rejitha R.S. | 2 | 16 | 2.81 |
| C. Preethi | 3 | 0 | 0.34 |
| C. Bency Bright | 4 | 0 | 0.34 |
| W. S. Judyfer | 5 | 0 | 0.34 |