GPU-based parallelisation of a versatile video coding adaptive loop filter in resource-constrained heterogeneous embedded platform

Abstract

This paper presents a GPU-based parallelisation of an optimised versatile video decoder (VVC) adaptive loop filter (ALF) filter on a resource-constrained heterogeneous platform. The GPU has been comprehensively utilised to maximise the degree of parallelism, making the programme capable of exploiting the GPU capabilities. The proposed approach enables to accelerate the ALF computation by an average of two times when compared to an already fully optimised version of the software decoder implementation over an embedded platform. Finally, this work presents an analysis of energy consumption, showing that the proposed methodology has a negligible impact on this key parameter.