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DEPO: A dynamic energy‐performance optimizer tool for automatic power capping for energy efficient high‐performance computing
Abstract
In the article we propose an automatic power capping software tool DEPO that allows one to perform runtime optimization of performance and energy related metrics. For an assumed application model with an initialization phase followed by a running phase with uniform compute and memory intensity, the tool performs automatic tuning engaging one of the two exploration algorithms—linear search (LS) and golden section search (GSS), finds a power cap optimizing a given metric and sets it for the remaining computations. The considered metrics include energy (E), energy-delay sum, energy-delay product. We present experimental results obtained for a set of benchmarks that differ in compute and memory intensity—parallel custom built OpenMP implementations of: numerical integration, heat distribution simulation (HEAT), fast Fourier transform (FFT), and additionally NAS parallel benchmarks: CG, MG, BT, SP, and LU. Tests were performed using multi-core CPUs that are representatives of modern servers and the desktop family: 2 Intel Xeon E5-2670 v3 CPU (Haswell-EP) and Intel i7-9700K CPU (Coffee Lake). The results show that our approach enabled considerable improvements for the tested metrics, for example, for HEAT and Coffee Lake we minimized energy by 50% at the cost of a 15% increase in execution time (LS), for FFT energy was minimized by 40% at a 25.5% increase in execution time (GSS), for SP and Haswell energy was minimized by 25% at the cost of an 18.5% time increase and for Coffee Lake energy was decreased by 56% with a 12% time increase.
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Details
- Category:
- Articles
- Type:
- artykuły w czasopismach
- Published in:
-
SOFTWARE-PRACTICE & EXPERIENCE
no. 52,
pages 2598 - 2634,
ISSN: 0038-0644 - Language:
- English
- Publication year:
- 2022
- Bibliographic description:
- Krzywaniak A., Czarnul P., Proficz J.: DEPO: A dynamic energy‐performance optimizer tool for automatic power capping for energy efficient high‐performance computing// SOFTWARE-PRACTICE & EXPERIENCE -Vol. 52,iss. 12 (2022), s.2598-2634
- DOI:
- Digital Object Identifier (open in new tab) 10.1002/spe.3139
- Sources of funding:
-
- Free publication
- Verified by:
- Gdańsk University of Technology
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