Input space adaptive design: a high-level methodology for energy and performance optimization

  • Authors:
  • Weidong Wang;Anand Raghunathan;Ganesh Lakshminarayana;Niraj K. Jha

  • Affiliations:
  • Dept. of Electrical Eng., Princeton University, NJ;NEC, C&C Research Labs, Princeton, NJ;NEC, C&C Research Labs, Princeton, NJ;Dept. of Electrical Eng., Princeton University, NJ

  • Venue:
  • Proceedings of the 38th annual Design Automation Conference
  • Year:
  • 2001

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Abstract

This paper presents a high-level design methodology, called input space adaptive design, and new design automation algorithms for optimizing energy consumption and performance. An input space adaptive design exploits the well-known fact that the quality of hardware circuits and software programs can be significantly optimized by employing algorithms and implementation architectures that adapt to the input statistics. We propose a methodology for such designs which includes identifying parts of the behavior to be optimized, selecting appropriate input sub-spaces, transforming the behavior, and verifying the equivalence of the original and optimized designs. Experimental results indicate that such designs can reduce energy consumption by up to 70.6% (average of 55.4%), and simultaneously improve performance by up to 85.1% (average of 58.1%), leading to a reduction in the energy-delay product by up to 95.6% (average of 80.7%), compared to well-optimized designs that do not employ such techniques.