An evolutionary scheduling approach for trading-off accuracy vs. verifiable energy in multicore processors

Liqat, Umer; Bankovic, Zorana; López García, Pedro y Hermenegildo, Manuel V. (2017). An evolutionary scheduling approach for trading-off accuracy vs. verifiable energy in multicore processors. "Logic Journal of the IGPL", v. 25 (n. 6); pp. 1006-1019. ISSN 1367-0751. https://doi.org/10.1093/jigpal/jzx048.

Descripción

Título: An evolutionary scheduling approach for trading-off accuracy vs. verifiable energy in multicore processors
Autor/es:
  • Liqat, Umer
  • Bankovic, Zorana
  • López García, Pedro
  • Hermenegildo, Manuel V.
Tipo de Documento: Artículo
Título de Revista/Publicación: Logic Journal of the IGPL
Fecha: Diciembre 2017
Volumen: 25
Materias:
Escuela: E.T.S. de Ingenieros Informáticos (UPM)
Departamento: Inteligencia Artificial
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

This work addresses the problem of energy-efficient scheduling and allocation of tasks in multicore environments, where the tasks can allow a certain loss in accuracy in the output, while still providing proper functionality and meeting an energy budget. This margin for accuracy loss is exploited by using computing techniques that reduce the work load, and thus can also result in significant energy savings. To this end, we use the technique of loop perforation, that transforms loops to execute only a subset of their original iterations, and integrate this technique into our existing optimization tool for energy-efficient scheduling. To verify that a schedule meets an energy budget, both safe upper and lower bounds on the energy consumption of the tasks involved are needed. For this reason, we use a parametric approach to estimate safe (and tight) energy bounds that are practical for energy verification (and optimization applications). This approach consists in dividing a program into basic (?branchless?) blocks, establishing the maximal (resp. minimal) energy consumption for each block using an evolutionary algorithm, and combining the obtained values according to the program control flow, by using static analysis to produce energy bound functions on input data sizes. The scheduling tool uses evolutionary algorithms coupled with the energy bound functions for estimating the energy consumption of different schedules. The experiments with our prototype implementation were performed on multicore XMOS chips, but our approach can be adapted to any multicore environment with minor changes. The experimental results show that our new scheduler enhanced with loop perforation improves on the previous one, achieving significant energy savings (31% on average for the test programs) for acceptable levels of accuracy loss.

Proyectos asociados

TipoCódigoAcrónimoResponsableTítulo
FP7318337ENTRARoskilde UniversitetWhole-Systems Energy Transparency
Gobierno de EspañaTIN2012-39391-C04-0StrongSoftUniversidad Politécnica de MadridSTRONGSOFT-CLIP: TECNOLOGIAS RIGUROSAS PARA SOFTWARE DE NUEVA GENERACION, ABIERTO Y FIABLE
Gobierno de EspañaTIN2015- 67522-C3-1-RTRACESIMDEA SoftwareTECNOLOGIAS Y HERRAMIENTAS PARA EL DESARROLLO DE SOFTWARE CONSCIENTE DE LOS RECURSOS, CORRECTO Y EFICIENTE
Comunidad de MadridM141047003N-GREENSSin especificarSin especificar

Más información

ID de Registro: 48671
Identificador DC: http://oa.upm.es/48671/
Identificador OAI: oai:oa.upm.es:48671
Identificador DOI: 10.1093/jigpal/jzx048
URL Oficial: https://academic.oup.com/jigpal/article-abstract/25/6/1006/4645008?redirectedFrom=fulltext
Depositado por: Memoria Investigacion
Depositado el: 29 Ene 2018 15:32
Ultima Modificación: 29 Ene 2018 15:32
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