"Worst-case design is one of the keys to practical engineering: create solutions that can always withstand all the most adverse conditions that could occur. Yet, the limitations of battery capacity, the slowing progress in CMOS technology energy efficiency, and the ever growing need for more computational power combine into a grim outlook for worst-case design in the future. This becomes even worse, when one considers the exploding non-recurring engineering costs and turns toward programmable systems—an economic necessity in most cases and yet a fundamentally less energy-efficient implementation option. This project pretends to revolutionize the way systems are design today introducing the concept of opportunistic approximations to fundamentally depart from the notion of a single worst-case design point. Opportunistic approximations enable a continuous adaptation of the processing characteristics (operation type, number and precision) to the actual operating conditions. By relaxing the processing load when possible, a significantly increase in the processing efficiency of advanced DSP (Digital Signal Processing) flexible implementations is expected. Particularly, for DSP systems running under highly varying situations. Making opportunistic approximations practical requires the combination of deep knowledge of DSP applications and low power flexible DSP architectures, expertise developed by the applicant during his PhD, with the latest design automation technology, area where the proposed host institution excels worldwide. Thus, enabling opportunistic approximations will result in major reductions of average energy consumption and average processing time while still meeting functional specifications at the input-output interface (e.g., maximal bit-error-rate for a wireless system)."
Field of science
- /engineering and technology/electrical engineering, electronic engineering, information engineering/electronic engineering/signal processing
Call for proposal
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