Author:
Klôh Vinícius,Gritz Matheus,Schulze Bruno,Ferro Mariza
Abstract
Performance and energy efficiency are now critical concerns in high performance scientific computing. It is expected that requirements of the scientific problem should guide the orchestration of different techniques of energy saving, in order to improve the balance between energy consumption and application performance. To enable this balance, we propose the development of an autonomous framework to make this orchestration and present the ongoing research to this development, more specifically, focusing in the characterization of the scientific applications and the performance modeling tasks using Machine Learning.
Publisher
Sociedade Brasileira de Computação
Cited by
2 articles.
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