Energy and Quality-Aware Multimedia Signal Processing

abstract: Today's mobile devices have to support computation-intensive multimedia applications with a limited energy budget. In this dissertation, we present architecture level and algorithm-level techniques that reduce energy consumption of these devices with minimal impact on system quality....

Full description

Bibliographic Details
Other Authors: Emre, Yunus (Author)
Format: Doctoral Thesis
Language:English
Published: 2012
Subjects:
Online Access:http://hdl.handle.net/2286/R.I.15781
id ndltd-asu.edu-item-15781
record_format oai_dc
spelling ndltd-asu.edu-item-157812018-06-22T03:03:21Z Energy and Quality-Aware Multimedia Signal Processing abstract: Today's mobile devices have to support computation-intensive multimedia applications with a limited energy budget. In this dissertation, we present architecture level and algorithm-level techniques that reduce energy consumption of these devices with minimal impact on system quality. First, we present novel techniques to mitigate the effects of SRAM memory failures in JPEG2000 implementations operating in scaled voltages. We investigate error control coding schemes and propose an unequal error protection scheme tailored for JPEG2000 that reduces overhead without affecting the performance. Furthermore, we propose algorithm-specific techniques for error compensation that exploit the fact that in JPEG2000 the discrete wavelet transform outputs have larger values for low frequency subband coefficients and smaller values for high frequency subband coefficients. Next, we present use of voltage overscaling to reduce the data-path power consumption of JPEG codecs. We propose an algorithm-specific technique which exploits the characteristics of the quantized coefficients after zig-zag scan to mitigate errors introduced by aggressive voltage scaling. Third, we investigate the effect of reducing dynamic range for datapath energy reduction. We analyze the effect of truncation error and propose a scheme that estimates the mean value of the truncation error during the pre-computation stage and compensates for this error. Such a scheme is very effective for reducing the noise power in applications that are dominated by additions and multiplications such as FIR filter and transform computation. We also present a novel sum of absolute difference (SAD) scheme that is based on most significant bit truncation. The proposed scheme exploits the fact that most of the absolute difference (AD) calculations result in small values, and most of the large AD values do not contribute to the SAD values of the blocks that are selected. Such a scheme is highly effective in reducing the energy consumption of motion estimation and intra-prediction kernels in video codecs. Finally, we present several hybrid energy-saving techniques based on combination of voltage scaling, computation reduction and dynamic range reduction that further reduce the energy consumption while keeping the performance degradation very low. For instance, a combination of computation reduction and dynamic range reduction for Discrete Cosine Transform shows on average, 33% to 46% reduction in energy consumption while incurring only 0.5dB to 1.5dB loss in PSNR. Dissertation/Thesis Emre, Yunus (Author) Chakrabarti, Chaitali (Advisor) Bakkaloglu, Bertan (Committee member) Cao, Yu (Committee member) Papandreou-Suppappola, Antonia (Committee member) Arizona State University (Publisher) Electrical engineering Low-Power Multimedia Video-Image VLSI eng 134 pages Ph.D. Electrical Engineering 2012 Doctoral Dissertation http://hdl.handle.net/2286/R.I.15781 http://rightsstatements.org/vocab/InC/1.0/ All Rights Reserved 2012
collection NDLTD
language English
format Doctoral Thesis
sources NDLTD
topic Electrical engineering
Low-Power
Multimedia
Video-Image
VLSI
spellingShingle Electrical engineering
Low-Power
Multimedia
Video-Image
VLSI
Energy and Quality-Aware Multimedia Signal Processing
description abstract: Today's mobile devices have to support computation-intensive multimedia applications with a limited energy budget. In this dissertation, we present architecture level and algorithm-level techniques that reduce energy consumption of these devices with minimal impact on system quality. First, we present novel techniques to mitigate the effects of SRAM memory failures in JPEG2000 implementations operating in scaled voltages. We investigate error control coding schemes and propose an unequal error protection scheme tailored for JPEG2000 that reduces overhead without affecting the performance. Furthermore, we propose algorithm-specific techniques for error compensation that exploit the fact that in JPEG2000 the discrete wavelet transform outputs have larger values for low frequency subband coefficients and smaller values for high frequency subband coefficients. Next, we present use of voltage overscaling to reduce the data-path power consumption of JPEG codecs. We propose an algorithm-specific technique which exploits the characteristics of the quantized coefficients after zig-zag scan to mitigate errors introduced by aggressive voltage scaling. Third, we investigate the effect of reducing dynamic range for datapath energy reduction. We analyze the effect of truncation error and propose a scheme that estimates the mean value of the truncation error during the pre-computation stage and compensates for this error. Such a scheme is very effective for reducing the noise power in applications that are dominated by additions and multiplications such as FIR filter and transform computation. We also present a novel sum of absolute difference (SAD) scheme that is based on most significant bit truncation. The proposed scheme exploits the fact that most of the absolute difference (AD) calculations result in small values, and most of the large AD values do not contribute to the SAD values of the blocks that are selected. Such a scheme is highly effective in reducing the energy consumption of motion estimation and intra-prediction kernels in video codecs. Finally, we present several hybrid energy-saving techniques based on combination of voltage scaling, computation reduction and dynamic range reduction that further reduce the energy consumption while keeping the performance degradation very low. For instance, a combination of computation reduction and dynamic range reduction for Discrete Cosine Transform shows on average, 33% to 46% reduction in energy consumption while incurring only 0.5dB to 1.5dB loss in PSNR. === Dissertation/Thesis === Ph.D. Electrical Engineering 2012
author2 Emre, Yunus (Author)
author_facet Emre, Yunus (Author)
title Energy and Quality-Aware Multimedia Signal Processing
title_short Energy and Quality-Aware Multimedia Signal Processing
title_full Energy and Quality-Aware Multimedia Signal Processing
title_fullStr Energy and Quality-Aware Multimedia Signal Processing
title_full_unstemmed Energy and Quality-Aware Multimedia Signal Processing
title_sort energy and quality-aware multimedia signal processing
publishDate 2012
url http://hdl.handle.net/2286/R.I.15781
_version_ 1718699857418387456