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Quality-Energy Aware Design of Approximate Computing Systems

Quality-Energy Aware Design of Approximate Computing Systems

Prof. Andreas Gerstlauer,
The University of Texas at Austin, USA


December 19th, 11:00  


Room H120 Technologiefabrik  

Approximate computing is an aggressive design technique aimed at achieving significant energy savings by trading off computational precision and accuracy in inherently error-tolerant applications. This introduces a new notion of quality as a fundamental design parameter. While ad-hoc solutions have been explored at various levels, systematic approaches that span across the compute stack are lacking. In this talk, we present recent work on investigating quality-energy aware system design all the way from basic hardware components to application-level specifications. We first present design strategies for approximate arithmetic units, such as adders and multipliers. A key observation is that there exists a large design space of Pareto-optimal solutions formed by novel methods for approximate Boolean logic synthesis. Such functional units then form the building blocks for approximate hardware and software processors. We further discuss approaches for approximating compilation and synthesis of high-level application models into quality-configurable software or hardware. There, accuracy levels are assigned to individual operations such that energy is minimized while meeting a generic output quality constraint. A key concern is a fast and accurate analytical estimation of arbitrary, application-specific quality metrics under general hardware approximations. The long-term goal is to integrate such optimizations into existing compiler and high-level synthesis frameworks. This in turn will provide the basis for developing novel approaches for combined mapping, scheduling and quality-energy-performance configuration of application tasks running on approximate system platforms. When applying such techniques to the design and optimization of signal processing systems, results at varying levels show that energy savings of 40% are possible while maintaining overall output quality.

Andreas Gerstlauer is an Associate Professor in Electrical and Computer Engineering at The University of Texas at Austin. He received his Dipl.-Ing. degree in Electrical Engineering from the University of Stuttgart, Germany, in 1997, and M.S. and Ph.D. degrees in information and computer science from the University of California, Irvine (UCI), in 1998 and 2004, respectively. Prior to joining UT Austin in 2008, he was an Assistant Researcher in the Center for Embedded Computer Systems (CECS) at UC Irvine, leading a research group to develop electronic system-level (ESL) design tools. Dr. Gerstlauer is co-author on 3 books and more than 65 conference and journal publications. His research interests include system-level design automation, system modeling, design languages and methodologies, and embedded hardware and software synthesis.