Spatio-Temporal Parallelization Scheme for HEVC Encoding on Multi-Computer Systems

Alexandre Mercat, Sami Ahovainio, Jarno Vanne

Tutkimustuotos: KonferenssiartikkeliScientificvertaisarvioitu

10 Lataukset (Pure)

Abstrakti

High Efficiency Video Coding (HEVC) sets the scene for economic video transmission and storage, but its inherent computational complexity calls for efficient parallelization techniques. This paper introduces and compares three different parallelization strategies for HEVC encoding on multi-computer systems: 1) spatial parallelization scheme, where input video frames are divided into slices and distributed among available computers; 2) temporal parallelization scheme, where input video is distributed among computers in groups of consecutive frames; 3) spatio-temporal parallelization scheme that combines the proposed spatial and temporal approaches. All these three schemes were benchmarked as part of the practical Kvazaar open-source HEVC encoder. Our experimental results on 2–5 computer configurations show that using the spatial scheme gives 1.65×–2.90× speedup at the cost of 4.16%–13.09% bitrate loss over a single-computer setup. The respective speedup with temporal parallelization is 1.86×–3.26× without any coding overhead. The spatio-temporal scheme with 2 slices was shown to offer the best load-balancing with 1.81×–3.55× speedups and a constant coding loss of 4.16%.
AlkuperäiskieliEnglanti
Otsikko2022 IEEE International Conference on Image Processing (ICIP)
JulkaisupaikkaBordeaux, France
KustantajaIEEE
ISBN (elektroninen)978-1-6654-9620-9
DOI - pysyväislinkit
TilaJulkaistu - 18 lokak. 2022
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaIEEE International Conference on Image Processing - Bordeaux, Ranska
Kesto: 16 lokak. 202219 lokak. 2022

Julkaisusarja

NimiProceedings : International Conference on Image Processing
ISSN (elektroninen)2381-8549

Conference

ConferenceIEEE International Conference on Image Processing
Maa/AlueRanska
KaupunkiBordeaux
Ajanjakso16/10/2219/10/22

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