  In recent years, the global demand for high-resolution videos and the
emergence of new multimedia applications have created the need for a new video
coding standard. Hence, in July 2020 the Versatile Video Coding (VVC) standard
was released providing up to 50% bit-rate saving for the same video quality
compared to its predecessor High Efficiency Video Coding (HEVC). However, this
bit-rate saving comes at the cost of a high computational complexity,
particularly for live applications and on resource-constraint embedded devices.
This paper presents two optimized VVC software decoders, named OpenVVC and
Versatile Video deCoder (VVdeC), designed for low resources platforms. They
exploit optimization techniques such as data level parallelism using Single
Instruction Multiple Data (SIMD) instructions and functional level parallelism
using frame, tile and slice-based parallelisms. Furthermore, a comparison in
terms of decoding run time, energy and memory consumption between the two
decoders is presented while targeting two different resource-constraint
embedded devices. The results showed that both decoders achieve real-time
decoding of Full High definition (FHD) resolution over the first platform using
8 cores and High-definition (HD) real-time decoding for the second platform
using only 4 cores with comparable results in terms of average consumed energy:
around 26 J and 15 J for the 8 cores and 4 cores embedded platforms,
respectively. Regarding the memory usage, OpenVVC showed better results with
less average maximum memory consumed during run time compared to VVdeC.
