Reduced energy decoding of MPEG streams

Mesarina, Malena; Turner, Yoshio

doi:10.1007/s00530-003-0090-7

Cited by 33 publications

(34 citation statements)

References 21 publications

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“…In particular, DVS is suitable for eliminating idle times during low workload periods. Recently, researchers have attempted to apply DVS to video decoding to reduce power [18,17,21,19,24,33].…”

Section: Dynamic Voltage Scaling (Dvs)mentioning

confidence: 99%

“…DVS has been proposed as a mean for a processor to deliver high performance when required, while significantly reducing power consumption during low workload periods [4,9,10,[12][13][14][15][16][17][18][19][20][21][22][23][24]33]. The advantage of DVS can be observed from the power consumption characteristics of digital static CMOS circuits [21] and the clock frequency equation [24]:…”

Section: Background On Dynamic Voltage Scaling (Dvs)mentioning

confidence: 99%

“…They utilize some form of a decoding time prediction algorithm to dynamically perform voltage scaling [18,17,21,24,32,33].…”

Section: Prediction-based Dvs Approaches For Low-power Video Decodingmentioning

confidence: 99%

“…It should be noted that the offline methods have one striking drawback in that they all require a priori knowledge of encoded frame sizes and therefore, need some sort of preprocessing. There is also a method that completely bypasses the decoding time prediction at the client to eliminate the possibilities of errors due to inaccurate scaling predictions [17]. This is done by preprocessing video streams off-line on media servers to add accurate video complexity information during the encoding process.…”

Section: Overview Of Dvs Approaches and Their Prediction Schemesmentioning

confidence: 99%

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Dynamic voltage scaling techniques for power efficient video decoding

Liu

Nurvitadhi

Dixit

et al. 2005

Journal of Systems Architecture

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This paper presents a comparison of power-aware video decoding techniques that utilize Dynamic Voltage Scaling (DVS) capability. 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. We propose 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. We compare this technique 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 a 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 power savings increase, but the number of deadline misses also increase as the number of processor settings used in a DVS algorithm are increased. More importantly, most of these deadline misses are within 10%-20% of the playout interval and thus insignificant. 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 should be sufficient to achieve near maximum performance with the experimental environment and the video workloads we have used.

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Section: Dynamic Voltage Scaling (Dvs)mentioning

confidence: 99%

Section: Background On Dynamic Voltage Scaling (Dvs)mentioning

confidence: 99%

“…They utilize some form of a decoding time prediction algorithm to dynamically perform voltage scaling [18,17,21,24,32,33].…”

Section: Prediction-based Dvs Approaches For Low-power Video Decodingmentioning

confidence: 99%

Section: Overview Of Dvs Approaches and Their Prediction Schemesmentioning

confidence: 99%

See 2 more Smart Citations

Dynamic voltage scaling techniques for power efficient video decoding

Liu

Nurvitadhi

Dixit

et al. 2005

Journal of Systems Architecture

View full text Add to dashboard Cite

show abstract

“…For instance, at the hardware level, processors can employ intelligent power management techniques that monitor the CPU usage and dynamically vary the CPU clock frequency based on the observed load [9,15]. A recent study has also proposed offline processing of MPEG video streams to determine the CPU voltage settings for each frame during decode time-the techniques lowers energy usage by choosing the smallest feasible CPU voltage setting for each frame so as to meet real-time decoding constraints [13]. At the operating system level, recent studies have investigated intelligent CPU scheduling techniques that lower the energy required to schedule a set a tasks [2,6].…”

Section: Related Workmentioning

confidence: 99%