Energy characterization and instruction-level energy model of Intel's Xeon Phi processor

Intel's Xeon Phi is the first commercial many-core/multi-thread x86--based processor. Xeon Phi belongs to a new breed of high performance computing processors that seek high compute density as well as energy efficiency. However, no high-level energy model is available for Xeon Phi software deve...

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Veröffentlicht in:Proceedings of the 2013 International Symposium on Low Power Electronics and Design S. 389 - 394
Hauptverfasser: Shao, Yakun Sophia, Brooks, David
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: Piscataway, NJ, USA IEEE Press 04.09.2013
Schriftenreihe:ACM Conferences
Schlagworte:
Applied computing > Physical sciences and engineering > Electronics
Hardware > Hardware validation
Hardware > Integrated circuits
Xeon Phi
energy characterization
instruction-level energy model
ISBN:1479912352, 9781479912353
Online-Zugang:Volltext
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Zusammenfassung:Intel's Xeon Phi is the first commercial many-core/multi-thread x86--based processor. Xeon Phi belongs to a new breed of high performance computing processors that seek high compute density as well as energy efficiency. However, no high-level energy model is available for Xeon Phi software developers to quickly evaluate and optimize energy efficiency. This work demonstrates an instruction-level energy model for the Xeon Phi processor to facilitate the development of energy-efficient software. In order to construct this model, we first characterize the energy consumption of the processor, identifying how energy per instruction scales with the number of cores, the number of active threads per core, and instruction types. Based on the energy characterization, we construct an instruction-level energy model and validate the accuracy of the model between 1% and 5% for real world benchmarks. We show that the energy model can be used to identify software inefficiencies for these benchmarks and find that Linpack code can be optimized to increase energy efficiency by as much as 10%.
ISBN:1479912352
9781479912353
DOI:10.5555/2648668.2648758