Low Power Embedded Software Optimization Using Symbolic Algebra

  • Authors:
  • A. Peymandoust;T. Simunic;G. de Micheli

  • Affiliations:
  • Computer Systems Laboratory, Stanford University, Stanford, CA;HP Labs & Stanford University, 1501 Page Mill Rd., MS 3U-4, Palo Alto, CA;Computer Systems Laboratory, Stanford University, Stanford, CA

  • Venue:
  • Proceedings of the conference on Design, automation and test in Europe
  • Year:
  • 2002

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Abstract

The market demand for portable multimediaapplications has exploded in the recent years.Unfortunately, for such applications current compilers andsoftware optimization methods often require designers todo part of the optimization manually. Specifically, thehigh-level arithmetic optimizations and the use of complexinstructions are left to the designers' ingenuity. In thispaper, we present a tool flow, SymSoft, that automates theoptimization of power-intensive algorithmic constructsusing symbolic algebra techniques combined with energyprofiling. SymSoft is used to optimize and tune thealgorithmic level description of an MPEG Layer III (MP3)audio decoder for the SmartBadge [2] portable embeddedsystem. We show that our tool lowers the number ofinstructions and memory accesses and thus lowers thesystem power consumption. The optimized MP3 audiodecoder software meets real-time constraints on theSmartBadge system with low energy consumption.Furthermore, the performance improves by a factor of 7.27and the energy consumption decreases by a factor of 4.45over the original executable specification.