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Scheduling and energy-distortion tradeoffs with operational refinement of image processing

Anastasia, D; Andreopoulos, Y; (2010) Scheduling and energy-distortion tradeoffs with operational refinement of image processing. In: Proceedings -Design, Automation and Test in Europe, DATE. (pp. 1719 - 1724).

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Abstract

Ubiquitous image processing tasks (such as transform decompositions, filtering and motion estimation) do not currently provide graceful degradation when their clock-cycles budgets are reduced, e.g. when delay deadlines are imposed in a multi-tasking environment to meet throughput requirements. This is an important obstacle in the quest for full utilization of modern programmable platforms' capabilities, since: (i) worst-case considerations must be in place for reasonable quality of results; (ii) throughput-distortion tradeoffs are not possible for distortion-tolerant image processing applications without cumbersome (and potentially costly) system customization. In this paper, we extend the functionality of the recently-proposed software framework for operational refinement of image processing (ORIP) and demonstrate its inherent throughput-distortion and energy-distortion scalability. Importantly, our extensions allow for such scalabilities at the software level, without needing hardware-specific customization. Extensive tests on a mainstream notebook computer and on OLPC's subnotebook ("xo-laptop") verify that the proposed designs provide for: (i) seamless quality-complexity scalability per video frame; (ii) up to 60% increase in processing throughput with graceful degradation in output quality; (iii) up to 20% more images captured and filtered for the same power-level reduction on the xo-laptop. © 2010 EDAA.

Type:Proceedings paper
Title:Scheduling and energy-distortion tradeoffs with operational refinement of image processing
UCL classification:UCL > School of BEAMS > Faculty of Engineering Science > Electronic and Electrical Engineering

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