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. Therefore, in July 2020, the versatile video coding (VVC) standard was released, providing up to 50% bit-rate savings for the same video quality compared to its predecessor high-efficiency video coding (HEVC). However, these bit-rate savings come at the cost of high computational complexity, particularly for live applications and on resource-constrained embedded devices. This paper evaluates two optimized VVC software decoders, named OpenVVC and Versatile Video deCoder (VVdeC), designed for low resources platforms. These decoders 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 of decoding runtime, 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 on 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 the average energy consumed: around 26 J and 15 J for the 8 cores and 4 cores platforms, respectively. Furthermore, OpenVVC showed better results regarding memory usage with a lower average maximum memory consumed during runtime than VVdeC.

近年来，全球对高分辨率视频的需求和新多媒体应用的出现催生了对新视频编码标准的需求。因此，2020 年 7 月，通用视频编码 (VVC) 标准发布，与之前的高效视频编码 (HEVC) 相比，在相同视频质量下可节省高达 50% 的码率。然而，这些比特率的节省是以高计算复杂性为代价的，特别是对于实时应用程序和资源有限的嵌入式设备。本文评估了两种优化的 VVC 软件解码器，名为 OpenVVC 和 Versatile Video deCoder (VVdeC)，专为低资源平台设计。这些解码器利用优化技术，例如使用单指令多数据 (SIMD) 指令的数据级并行性以及使用基于帧、图块和片的并行性的功能级并行性。此外，还针对两种不同的资源约束嵌入式设备，对两种解码器之间的解码运行时间、能量和内存消耗进行了比较。结果表明，两个解码器在使用 8 核的第一个平台上实现了全高清 (FHD) 分辨率的实时解码，在仅使用 4 个核的第二个平台上实现了高清 (HD) 实时解码，并且在平均能耗方面：8核和4核平台分别约为26 J和15 J。此外，OpenVVC 在内存使用方面表现出更好的结果，运行时消耗的平均最大内存比 VVdeC 更低。