Multi-Level Parallelization Scheme for Distributed HEVC Encoding on Multi-Computer Systems

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) spatiotemporal parallelization scheme that combines the proposed spatial and temporal approaches. All these three schemes were benchmarked as part of the practical Kvazaar opensource 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%.

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“…The first version of our encoding parallelization framework was introduced in [13], [14]. It supported process level parallelization.…”

Section: Introductionmentioning

confidence: 99%

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

Mercat

Ahovainio

Vanne

2022

2022 IEEE International Conference on Image Processing (ICIP)

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Multi-Level Parallelization Scheme for Distributed HEVC Encoding on Multi-Computer Systems

Cited by 1 publication

References 18 publications

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

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

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