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 wellknown 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.
All Science Journal Classification (ASJC) codes
- Hardware and Architecture
- Control and Systems Engineering