Dynamic Voltage Scaling Techniques for Power Efficient Video Decoding

This paper presents a comparison of power-aware video decoding techniques that utilize dynamic voltage scaling (DVS). These techniques reduce the power consumption of a processor by exploiting high frame variability within a video stream. This is done through scaling of the voltage and frequency of the processor during the video decoding process. However, DVS causes frame deadline misses due to inaccuracies in decoding time predictions and granularity of processor settings used. Four techniques were simulated and compared in terms of power consumption, accuracy, and deadline misses. In addition, this paper proposes the frame-data computation aware (FDCA) technique, which is a useful power-saving technique not only for stored video but also for real-time video applications. The FDCA method is compared with the GOP, Direct, and Dynamic methods, which tend to be more suited for stored video applications. The simulation results indicated that the Dynamic per-frame technique, where the decoding time prediction adapts to the particular video being decoded, provides the most power saving with performance comparable to the ideal case. On the other hand, the FDCA method consumes more power than the Dynamic method but can be used for stored video and real-time time video scenarios without the need for any preprocessing. Our findings also indicate that, in general, DVS improves power savings, but the number of deadline misses also increase as the number of available processor settings increases. More importantly, most of these deadline misses are within 10–20% of the playout interval and thus have minimal affect on video quality. However, video clips with high variability in frame complexities combined with inaccurate decoding time predictions may degrade the video quality. Finally, our results show that a processor with 13 voltage/frequency settings is sufficient to achieve near maximum performance with the experimental environment and the video workloads we have used

Dynamic Voltage Scaling Techniques for Power Efficient Video Decoding

This paper presents a comparison of power-aware video decoding techniques that utilize dynamic voltage scaling (DVS). These techniques reduce the power consumption of a processor by exploiting high frame variability within a video stream. This is done through scaling of the voltage and frequency of the processor during the video decoding process. However, DVS causes frame deadline misses due to inaccuracies in decoding time predictions and granularity of processor settings used. Four techniques were simulated and compared in terms of power consumption, accuracy, and deadline misses. In addition, this paper proposes the frame-data computation aware (FDCA) technique, which is a useful power-saving technique not only for stored video but also for real-time video applications. The FDCA method is compared with the GOP, Direct, and Dynamic methods, which tend to be more suited for stored video applications. The simulation results indicated that the Dynamic per-frame technique, where the decoding time prediction adapts to the particular video being decoded, provides the most power saving with performance comparable to the ideal case. On the other hand, the FDCA method consumes more power than the Dynamic method but can be used for stored video and real-time time video scenarios without the need for any preprocessing. Our findings also indicate that, in general, DVS improves power savings, but the number of deadline misses also increase as the number of available processor settings increases. More importantly, most of these deadline misses are within 10–20% of the playout interval and thus have minimal affect on video quality. However, video clips with high variability in frame complexities combined with inaccurate decoding time predictions may degrade the video quality. Finally, our results show that a processor with 13 voltage/frequency settings is sufficient to achieve near maximum performance with the experimental environment and the video workloads we have used

Green computing: power optimisation of VFI-based real-time multiprocessor dataflow applications (extended version)

Execution time is no longer the only performance metric for computer systems. In fact, a trend is emerging to trade raw performance for energy savings. Techniques like Dynamic Power Management (DPM, switching to low power state) and Dynamic Voltage and Frequency Scaling (DVFS, throttling processor frequency) help modern systems to reduce their power consumption while adhering to performance requirements. To balance flexibility and design complexity, the concept of Voltage and Frequency Islands (VFIs) was recently introduced for power optimisation. It achieves fine-grained system-level power management, by operating all processors in the same VFI at a common frequency/voltage.This paper presents a novel approach to compute a power management strategy combining DPM and DVFS. In our approach, applications (modelled in full synchronous dataflow, SDF) are mapped on heterogeneous multiprocessor platforms (partitioned in voltage and frequency islands). We compute an energy-optimal schedule, meeting minimal throughput requirements. We demonstrate that the combination of DPM and DVFS provides an energy reduction beyond considering DVFS or DMP separately. Moreover, we show that by clustering processors in VFIs, DPM can be combined with any granularity of DVFS. Our approach uses model checking, by encoding the optimisation problem as a query over priced timed automata. The model-checker Uppaal Cora extracts a cost minimal trace, representing a power minimal schedule. We illustrate our approach with several case studies on commercially available hardware

Recent advances in the hardware architecture of flat display devices

Thesis (Master)--Izmir Institute of Technology, Electronics and Communication Engineering, Izmir, 2007Includes bibliographical References (leaves: 115-117)Text in English; Abstract: Turkish and Englishxiii, 133 leavesThesis will describe processing board hardware design for flat panel displays with integrated digital reception, the design challenges in flat panel displays with integrated digital reception explained with details. Thesis also includes brief explanation of flat panel technology and processing blocks. Explanations of building blocks of TV and flat panel displays are given before design stage for better understanding of design stage. Hardware design stage of processing board is investigated in two major steps, schematic design and layout design. First step of the schematic design is system level block diagram design. Schematic diagram is the detailed application level hardware design and layout is the implementation level of the design. System level, application level and implementation level hardware design of the TV processing board is described with details in thesis. Design challenges, considerations and solutions are defined in advance for flat panel displays

Novel VLSI Architecture for Quantization and Variable Length Coding for H-264/AVC Video Compression Standard

Integrated multimedia systems process text, graphics, and other discrete media such as digital audio and video streams. In an uncompressed state, graphics, audio and video data, especially moving pictures, require large transmission and storage capacities which can be very expensive. Hence video compression has become a key component of any multimedia system or application. The ITU (International Telecommunications Union) and MPEG (Moving Picture Experts Group) have combined efforts to put together the next generation of video compression standard, the H.264/MPEG-4 PartlO/AVC, which was finalized in 2003. The H.264/AVC uses significantly improved and computationally intensive compression techniques to maximize performance. H.264/AVC compliant encoders achieve the same reproduction quality as encoders that are compliant with the previous standards while requiring 60% or less of the bit rate [2]. This thesis aims at designing two basic blocks of an ASIC capable of performing the H.264 video compression. These two blocks, the Quantizer, and Entropy Encoder implement the Baseline Profile of the H.264/AVC standard. The architecture is implemented in Register Transfer Level HDL and synthesized with Synopsys Design Compiler using TSMC 0.25(xm technology, giving us an estimate of the hardware requirements in real-time implementation. The quantizer block is capable of running at 309MHz and has a total area of 785K gates with a power requirement of 88.59mW. The entropy encoder unit is capable of running at 250 MHz and has a total area of 49K gates with a power requirement of 2.68mW. The high speed that is achieved in this thesis simply indicates that the two blocks Quantizer and Entropy Encoder can be used as IP embedded in the HDTV systems

Power-Aware HEVC Decoding with Tunable Image Quality

International audienceA high pressure is put on mobile devices to support increasingly advanced applications requiring more processing capabilities. Among those, the emerging High Efficiency Video Coding (HEVC) provides a better video quality for the same bit rate than the previous H.264 standard. A limitation in the usability of a mobile video playing device is the lack of support for guaranteeing stand-by time and up time for battery driven devices. The Green Metadata initiative within the MPEG standard was launched to address the power saving issues of the decoder and defines the technology requirements. In this paper, we propose a HEVC decoder with tunable decoding quality levels for maximum power savings as suggested in the scope of the Green Metadata initiative. Our experiments reveal that the modified HEVC video decoder can save up to 28 % of power consumption in real-world platforms while keeping better quality than decoding with H.264