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Memorias de investigación
Conferencias:
Inferring Parametric Energy Consumption Functions at Different Software Levels: ISA vs. LLVM IR.
Año:2016
Áreas de investigación
  • Ciencias de la computación y tecnología informática
Datos
Descripción
The static estimation of the energy consumed by program executions is an important challenge, which has applications in program optimization and verification, and is instrumental in energy-aware software development. Our objective is to estimate such energy consumption in the form of functions on the input data sizes of programs. We have developed a tool for experimentation with static analysis which infers such energy functions at two levels, the instruction set architecture (ISA) and the intermediate code (LLVM IR) levels, and reflects it upwards to the higher source code level. This required the development of a translation from LLVM IR to an intermediate representation and its integration with existing components, a translation from ISA to the same representation, a resource analyzer, an ISA-level energy model, and a mapping from this model to LLVM IR. The approach has been applied to programs written in the XC language running on XCore architectures, but is general enough to be applied to other languages. Experimental results show that our LLVM IR level analysis is reasonably accurate (less than 6.4% average error vs. hardware measurements) and more powerful than analysis at the ISA level. This paper provides insights into the trade-off of precision versus analyzability at these levels.
Internacional
Si
ISSN o ISBN
978-3-319-46559-3
Entidad relacionada
Nacionalidad Entidad
Sin nacionalidad
Lugar del congreso
Esta actividad pertenece a memorias de investigación
Participantes
  • Autor: Umer Liqat . (UPM)
  • Autor: Kyriakos Georgiou
  • Autor: Steve Kerrison
  • Autor: Pedro Lopez Garcia (UPM)
  • Autor: John P. Gallagher
  • Autor: Manuel de Hermenegildo Salinas (UPM)
  • Autor: Kerstin Eder
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Departamento: Inteligencia Artificial
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