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A Comprehensive Review of Software and Hardware Energy Efficiency of Video Decoders

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arxiv 2402.09001 v1 pith:HDDPCTHL submitted 2024-02-14 eess.IV

classification eess.IV
keywords energydemandsoftwarevideodecoderimplementationscompareddecoders
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Energy and compression efficiency are two essential parts of modern video decoder implementations that have to be considered. This work comprehensively studies the following six video coding formats regarding compression and decoding energy efficiency: AVC, VP9, HEVC, AV1, VVC, and AVM. We first evaluate the energy demand of reference and optimized software decoder implementations. Furthermore, we consider the influence of the usage of SIMD instructions on those decoder implementations. We find that AV1 is a sweet spot for optimized software decoder implementations with an additional energy demand of 16.55% and bitrate savings of -43.95% compared to VP9. We furthermore evaluate the hardware decoding energy demand of four video coding formats. Thereby, we show that AV1 has energy demand increases by 117.50% compared to VP9. For HEVC, we found a sweet spot in terms of energy demand with an increase of 6.06% with respect to VP9. Relative to their optimized software counterparts, hardware video decoders reduce the energy consumption to less than 9% compared to software decoders.

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Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Application Space and the Rate-Distortion-Complexity Analysis of Neural Video CODECs

    eess.IV 2025-09 conditional novelty 5.0 of 10

    A rate-distortion-complexity framework maps applications to (lambda,gamma) weights and shows only five of 17 neural video codecs can be optimal under the chosen complexity metric.

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