Abstract
The emergence of power efficiency as a primary constraint in processor and system designs poses new challenges concerning power and energy awareness for numerical libraries and scientific applications. Power consumption also plays a major role in the design of data centers in particular for peta- A nd exa-scale systems. Understanding and improving the energy efficiency of numerical simulation becomes very crucial. We present a detailed study and investigation toward controlling power usage and exploring how different power caps affect the performance of numerical algorithms with different computational intensities, and determine the impact and correlation with performance of scientific applications. Our analyses is performed using a set of representatives kernels, as well as many highly used scientific benchmarks. We quantify a number of power and performance measurements, and draw observations and conclusions that can be viewed as a roadmap toward achieving energy efficiency computing algorithms.
Original language | English |
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Title of host publication | 2017 IEEE High Performance Extreme Computing Conference, HPEC 2017 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9781538634721 |
DOIs | |
State | Published - Oct 30 2017 |
Event | 2017 IEEE High Performance Extreme Computing Conference, HPEC 2017 - Waltham, United States Duration: Sep 12 2017 → Sep 14 2017 |
Publication series
Name | 2017 IEEE High Performance Extreme Computing Conference, HPEC 2017 |
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Conference
Conference | 2017 IEEE High Performance Extreme Computing Conference, HPEC 2017 |
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Country/Territory | United States |
City | Waltham |
Period | 09/12/17 → 09/14/17 |
Funding
This material is based upon work supported in part by the National Science Foundation NSF under awards No. 1450429 "Performance Application Programming Interface for Extreme-scale Environments (PAPI-EX)" and No. 1514286.