Profiling and Autotuning for Energy-Aware Approximate Programming

One promising approach to energy-efficient computation, approximate computing, trades off output precision for gains in energy efficiency. Many applications can easily tolerate small errors, especially if they are handled in a disciplined manner. However, approximation introduces an inherent trade-off between quality of result and energy efficiency. Existing approaches lack ways to quantify and study these tradeoffs. This paper proposes tools to prototype, profile, and automati-cally tune the quality of programs designed to run on future approximate hardware. We describe the software layers re-quired in such a system and discuss design considerations. We built an OCaml-based prototype of our set of tools and performed three case studies. 1