COFFEE: compiler framework for energy-aware exploration

  • Authors:
  • Praveen Raghavan;Andy Lambrechts;Javed Absar;Murali Jayapala;Francky Catthoor;Diederik Verkest

  • Affiliations:
  • IMEC vzw, Heverlee, Belgium and ESAT, KU Leuven, Leuven, Belgium;IMEC vzw, Heverlee, Belgium and ESAT, KU Leuven, Leuven, Belgium;IMEC vzw, Heverlee, Belgium and ESAT, KU Leuven, Leuven, Belgium and ST Microelectronics, Singapore;IMEC vzw, Heverlee, Belgium;IMEC vzw, Heverlee, Belgium and ESAT, KU Leuven, Leuven, Belgium;IMEC vzw, Heverlee, Belgium and ESAT, KU Leuven, Leuven, Belgium and Dept. of Electrical Engineering, VUB, Brussels, Belgium

  • Venue:
  • HiPEAC'08 Proceedings of the 3rd international conference on High performance embedded architectures and compilers
  • Year:
  • 2008

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Abstract

Modern mobile devices need to be extremely energy efficient. Due to the growing complexity of these devices, energy aware design exploration has become increasingly important. Current exploration tools often do not support energy estimation, or require the design to be very detailed before the estimate is possible. It is important to get early feedback on both performance and energy consumption during all phases of the design and at higher abstraction levels. This paper presents a unified optimization and exploration framework, from source level transformation to processor architecture design. The proposed retargetable compiler and simulator framework can map applications to a range of processors and memory configurations, simulate and report detailed performance and energy estimates. An accurate energy modeling approach is introduced, which can estimate the energy consumption of processor and memories at a component level, which can help to guide the design process. Fast energy-aware architecture exploration is illustrated using an example processor. The flow is demonstrated using a representative wireless benchmark on two state of the art processors and on a processor with advanced low power extensions for memories. The framework also supports exploration of various novel low power extensions and their combinations. We show that a unified framework enables fast feedback on the effect of source level transformations of the application code on the final cycle count and energy consumption.