Observatorio de I+D+i UPM

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%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
DOI	10.1007/978-3-319-46559-3_5
Edición del Libro
Editorial del Libro	Springer, Cham
ISBN	978-3-319-46558-6
Serie
Título del Libro	Foundational and Practical Aspects of Resource Analysis: 4th International Workshop, FOPARA 2015
Desde página	81
Hasta página	100

Esta actividad pertenece a memorias de investigación

• Autor: Umer Liqat (IMDEA Software)
• Autor: K. Georgiou
• Autor: S. Kerrison
• Autor: Manuel de Hermenegildo Salinas (UPM)
• Autor: Pedro López García (IMDEA Software)
• Autor: john Patrick Gallagher (IMDEA Software)
• Autor: Kristin Eder

• Creador: Grupo de Investigación: Computación lógica, Lenguajes, Implementación y Paralelismo (CLIP)
• Departamento: Inteligencia Artificial