Liqat, U., Georgiou, K., Kerrison, S., Lopez-Garcia, P., Gallagher, John P., Hermenegildo, M.V., and Eder, K. (2016) Inferring Parametric Energy Consumption Functions at Different Software Levels: ISA vs. LLVM IR. In: Lecture Notes in Computer Science (9964) pp. 81-100. From: FOPARA 2015: 4th International Workshop on Foundational and Practical Aspects of Resource Analysis, 11 April 2015, London, UK.

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Abstract

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 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.

Item ID:	68076
Item Type:	Conference Item (Research - E1)
ISBN:	978-3-319-46559-3
Copyright Information:	© Springer International Publishing Switzerland 2016
Date Deposited:	24 Mar 2025 23:48
FoR Codes:	46 INFORMATION AND COMPUTING SCIENCES > 4606 Distributed computing and systems software > 460606 Energy-efficient computing @ 50% 46 INFORMATION AND COMPUTING SCIENCES > 4612 Software engineering > 461206 Software architecture @ 50%
SEO Codes:	22 INFORMATION AND COMMUNICATION SERVICES > 2204 Information systems, technologies and services > 220404 Computer systems @ 50% 17 ENERGY > 1701 Energy efficiency > 170102 Industrial energy efficiency @ 50%
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