Estimating the HEVC decoding energy using the decoder processing time

Herglotz, Christian; Walencik, Elisabeth; Kaup, André

doi:10.1109/iscas.2015.7168683

Cited by 15 publications

(14 citation statements)

References 3 publications

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“…In [7], the authors analyse the HEVC decoder complexity to devise a tile partitioning method capable of achieving load balancing in multicore platforms with speedup gains and energy savings. A linear relation between processing time and energy consumption was found in [8], bringing relevant insight for developing software-based decoders. Based on the high correlation between processing times and energy consumption, the energy savings between different implementations can be directly estimated from speedup gains in processing time.…”

mentioning

confidence: 87%

“…Using likwid-perfctrs marker API it is possible to measure the energy consumption of selected functions of an application by turning on/off hardware performance counters, which allows to obtain the CPU energy consumption per frame. Even though these tests were performed with minimal interference of other running processes, to minimize the impact of kernel processes on the intended measurements, the results were obtained running the same test several times (e.g., [6][7][8] and then normalising the average results. Also to get more accurate measurements, these started at each frame's first call of the decode method (class TDecTop) and finished after the execution of loop filters, when frames are fully reconstructed.…”

Section: Estimation Of Energy Consumptionmentioning

confidence: 99%

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A pixel-based complexity model to estimate energy consumption in video decoders

Costa

Assunção

Cordeiro

2018

2018 IEEE International Conference on Consumer Electronics (ICCE)

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Abstract-The increasing use of HEVC video streams in diverse multimedia applications is driving the need for higher user control and management of energy consumption in batterypowered devices. This paper presents a contribution for the lack of adequate solutions by proposing a pixel-based complexity model that is capable of estimating the energy consumption of an arbitrary software-based HEVC decoder, running on different hardware platforms and devices. In the proposed model, the computational complexity is defined as a linear function of the number of pixels processed by the main decoding functions, using weighting coefficients which represent the average computational effort that each decoding function requires per pixel. The results shows that the cross-correlation of frame-based complexity estimation with energy consumption is greater than 0.86. The energy consumption of video decoding is estimated with the proposed model within an average deviation range of about 6.9%, for different test sequences.

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mentioning

confidence: 87%

Section: Estimation Of Energy Consumptionmentioning

confidence: 99%

A pixel-based complexity model to estimate energy consumption in video decoders

Costa

Assunção

Cordeiro

2018

2018 IEEE International Conference on Consumer Electronics (ICCE)

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“…Thus, detailed and accurate modelling of the decoding operation complexity is crucially important. To similar ends, the state-of-the-art techniques have exploited high-level complexity analysis of decoding operations [23], energy estimation based on decoding time [24], and mapping of decoding energy to the content and QP [25]. Yet, the level of details in these models is inadequate for a Coding Unit (CU) level decoding complexity estimation.…”

Section: Decoding Complexity -Rate -Distortion Analysis For Encomentioning

confidence: 99%

Decoding-Complexity-Aware HEVC Encoding Using a Complexity–Rate–Distortion Model

Mallikarachchi

Talagala

Arachchi

et al. 2018

IEEE Trans. Consumer Electron.

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Abstract-The energy consumption of Consumer Electronic (CE) devices during media playback is inexorably linked to the computational complexity of decoding compressed video. Reducing a CE device's the energy consumption is therefore becoming ever more challenging with the increasing video resolutions and the complexity of the video coding algorithms. To this end, this paper proposes a framework that alters the video bit stream to reduce the decoding complexity and simultaneously limits the impact on the coding efficiency. In this context, this paper (i) first performs an analysis to determine the trade-off between the decoding complexity, video quality and bit rate with respect to a reference decoder implementation on a General Purpose Processor (GPP) architecture. Thereafter, (ii) a novel generic decoding complexity-aware video coding algorithm is proposed to generate decoding complexity-rate-distortion optimized High Efficiency Video Coding (HEVC) bit streams. The experimental results reveal that the bit streams generated by the proposed algorithm achieve 29.43% and 13.22% decoding complexity reductions for a similar video quality with minimal coding efficiency impact compared to the state-of-the-art approaches when applied to the HM16.0 and openHEVC decoder implementations, respectively. In addition, analysis of the energy consumption behavior for the same scenarios reveal up to 20% energy consumption reductions while achieving a similar video quality to that of HM 16.0 encoded HEVC bit streams.

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“…Crucially, such frameworks require an accurate and detailed complexity estimation model that predicts the processing requirements of the decoder. The state-of-the-art models for the complexity estimation include approaches such as predicting the decoding energy of a bit stream using the decoder processing time [9], and the mapping of the relationships between the decoder complexity, content and the QP [10]. Moreover, Herglotz et al introduce two such models [11], [12] that estimate the HEVC decoding energy for intra-and inter-coded frames, respectively.…”

Section: Introductionmentioning

confidence: 99%

A feature based complexity model for decoder complexity optimized HEVC video encoding

Mallikarachchi

Talagala

Arachchi

et al. 2017

2017 IEEE International Conference on Consumer Electronics (ICCE)

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The complexity of the novel video compression algorithms is a major contributor for the increased demand of processing and energy resources for video playback in consumer electronic devices. Therefore, a decoder complexity reduction mechanism is proposed which constitutes a model that predicts the decoder's complexity requirements to decode the HEVC encoded bit streams with a 4.2% average prediction error and a decoder complexity optimized encoding algorithm, which reduces the decoding complexity by an average of 28.06% and 41.19% with a-1.91 dB and-2.46 dB impact to the BD-PSNR for the low delay P and random access configurations, respectively.

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Estimating the HEVC decoding energy using the decoder processing time

Cited by 15 publications

References 3 publications

A pixel-based complexity model to estimate energy consumption in video decoders

A pixel-based complexity model to estimate energy consumption in video decoders

Decoding-Complexity-Aware HEVC Encoding Using a Complexity–Rate–Distortion Model

A feature based complexity model for decoder complexity optimized HEVC video encoding

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