Frame-based dynamic voltage and frequency scaling for a MPEG decoder

Choi, Kihwan; Dantu, Karthik; Cheng, Wei‐Chung; Pedram, Massoud

doi:10.1145/774572.774680

Cited by 105 publications

(90 citation statements)

References 22 publications

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“…It also shows consistently that the same codes can consume more energy when executed with higher frequency, and vice versa. These two experiments on the H.264 decoder imply that it would be effective to elaborate upon the get_block() and change the power modes properly according to the picture types like I, P, B as the previous works [17]. This implication is also meaningful in that the time-triggered approach for the function level energy measurement properly works and gives consistent energy consumption profiles on the DVSapplied program codes running upon the platforms supporting multiple power domains.…”

Section: Timing Analysismentioning

confidence: 74%

Experimental Analysis on Time-Triggered Power Consumption Measurement with DVS-Enabled Multiple Power Domain Platform

Chae

Kim

Jung

et al. 2007

Software Technologies for Embedded and Ubiquitous Systems

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Abstract.Recently, the battery and low-power H/W technologies for mobile and wearable computing devices have been advanced rapidly. But on the other hand the computation and communication demands of the embedded applications are increasing more rapidly. Therefore, the application developers are still required to develop their codes to utilize the available energy as efficient as possible. The provision of software power measurement with reasonable accuracy, consistency and low overhead is an indispensable factor for software power engineering. In this paper, we present a time-triggered mechanism for providing energy consumption profiles in the level of C functions. The similar mechanisms have already been introduced at the previous researches such as PowerScope and ePRO. Instead, we, in this paper, introduce our efforts to extend these researches to incorporate power domains and DVS(Dynamic Voltage Scaling), then interpret these mechanisms as the view of time-triggered approach for better understanding to the relationships among timer interrupt, context switching, DAQ triggering, multi-channel DAQ delay, and etc. From our experimental results, we could conclude that the timetriggered approach for the function level energy measurement properly worked with low overheads and produced consistent energy consumption profiles on the DVS-applied program codes running upon the platforms supporting multiple power domains.

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Section: Timing Analysismentioning

confidence: 74%

Experimental Analysis on Time-Triggered Power Consumption Measurement with DVS-Enabled Multiple Power Domain Platform

Chae

Kim

Jung

et al. 2007

Software Technologies for Embedded and Ubiquitous Systems

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show abstract

“…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%

“…Moreover, it is not useful in case of existing streams that may not include the video complexity information. Choi et al [32] have proposed a method in which the frame is divided into a frame-dependent and frame-independent part and scale voltage accordingly.…”

Section: Overview Of Dvs Approaches and Their Prediction Schemesmentioning

confidence: 99%

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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“…RELATED WORK Previous work in the domain of application specific power management mainly focused on video playback applications. In this context, control theoretic approaches like PID controllers and more complex algorithms (see [1], [2], [6]) have been successfully utilized to predict the decoders upcoming workloads. These video-specific algorithms rely on buffering frames which is not a feasible approach for game applications.…”

Section: Introductionmentioning

confidence: 99%

Managing power for closed-source android os games by lightweight graphics instrumentation

Dietrich¹,

Chakraborty²

2012

2012 11th Annual Workshop on Network and Systems Support for Games (NetGames)

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Abstract-Power consumption and battery life are important design concerns for mobile platforms. On these devices games can be considered as one of the most demanding applications in terms of computational cost and consumed energy. In this demo we showcase Android-based power management for games. We reduce the power consumption of games by scaling the processor's voltage and frequency. Towards this, the game's future workload has to be predicted. To accurately predict the workload, previous work heavily instrumented the game's source code itself. The source code is typically not available for up-todate Android games. The work presented in this paper does not require any modification of the game's source code and therefore can as well be applied to closed source games. Towards this, we utilize the game's communication interfaces with the operating system to accurately predict a game's workload. The approach presented in the following has been implemented and tested on the PandaBoard ES [12] and Galaxy Nexus mobile phone with a number of popular closed-source games. Measurements show significant power savings while the gaming experience is maintained.

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Frame-based dynamic voltage and frequency scaling for a MPEG decoder

Abstract: This paper describes a dynamic voltage and frequency scaling (DVFS

Cited by 105 publications

References 22 publications

Experimental Analysis on Time-Triggered Power Consumption Measurement with DVS-Enabled Multiple Power Domain Platform

Experimental Analysis on Time-Triggered Power Consumption Measurement with DVS-Enabled Multiple Power Domain Platform

Dynamic voltage scaling techniques for power efficient video decoding

Managing power for closed-source android os games by lightweight graphics instrumentation

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