## 5 Discussion  
The new video coding standard VVC introduces numerous advantages in video processing technology. However, it also brings increased computational complexity compared to its predecessor. In this section, a comparative study of the complexity analysis of our HGPP- and EGPP-based implementations of VTM8.0 with other VVC decoder implementations is presented. The maximum and minimum numbers of fps are compared for different implementations of the VVC decoder in Table 8. To fairly compare, only solutions from the reference coding software for A-class resolution sequences with the QP 22, 27, 32 and 37 were included in this section. To the best of our knowledge, no other VVC implementations based on a source code different from VTM8.0 have been reported in the scientific literature. In [17], the complexity analysis of the VTM5.0 decoder was illustrated using a core i9-9900X HGPP with a clock speed of 3.5 GHz. This implementation decoded between 1.3 and 4.2 fps for RA sequences of A-Class resolution with four QP values 22 to 37. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & **Conf.** & **CRY** & **VBC** & **DeC** & **LCF** & **CHCF** & **CRCF** & **OT** \\ \hline \multirow{2}{*}{HGPP} & AI & 8.3 & 1.4 & 17.5 & 37.7 & 10.7 & 22.9 & 1.5 \\  & RA & 12.6 & 1.4 & 21.6 & 43.2 & 8.0 & 11.6 & 1.6 \\ \hline \multirow{2}{*}{EGPP} & AI & 0.8 & 0.8 & 10.7 & 66.4 & 16.6 & 3.9 & 0.8 \\  & RA & 1.1 & 0.8 & 11.8 & 72.1 & 11.5 & 1.9 & 0.8 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Average processing times (in %) for the ALF block profiled over the HGPP and EGPP. Figure 12: Average time distribution for different parts of the adaptive loop filter (in %) over the EGPP. A HGPP core of an i7-8700K 4.7 GHz processor was used in [16] to analyse the complexity of a decoder based on VTM6.1. In this previous study, A-class sequences of RA configurations with QPs: 22, 27, 32, 37 were used as test benches. Additionally, an optimized complexity analysis was reported using RTX 2080 Ti 1.6 GHz GPU. Decoding ratios of 1.7 to 4.7 fps and of 2.1 to 8.4 fps were obtained for unoptimized and optimized decoder versions, respectively. In [5], a core i7-4790K 4.0 GHz HGPP was used to profile an implementation of a VTM6.0 decoder, but the global fps or processing times were not reported in this paper. As a result, it would not have been possible to make a fair comparison in terms of fps, but later in this section, it is used to compare the computational load among functional blocks. In our study, HGPP- and EGPP-based VTM8.0 complexity analyses were carried out. A-class sequences with four QP values 22, 27, 32, 37 were used, obtaining ratios between 0.6 and 2.3 fps, and between 1.2 and 4.1 fps over the HGPP, respectively, for the AI and RA configurations. In addition, decoding ratios of 0.3 to 0.8 fps and from 0.4 to 1.2 fps were obtained over the EGPP for the AI and RA configurations, respectively. The sequence with minimum-maximum (min-max) fps over the HGPP was similar to that of [17] for RA configurations, as both implementations used an HGPP with similar clock speeds. In addition, the min-max fps of [16] for RA configurations was approximately \(\times\)1.2 than our HGPP implementation, as the clock speed of the HGPP used in the previous study implementation was \(\times\)1.4 than our HGPP. Moreover, the GPU-based optimized solution of the previous study obtained almost double the min-max fps obtained with our HGPP implementation. In summary, the obtained fps for the RA configurations over all HGPP-based implementations varied slightly due to the different processor resources, which included clock speed or cache memory, among others. Additionally, an approximately double increase in speed was achieved using a GPU. However, for RA configurations, fps obtained over HGPP with respect to EGPP was roughly \(\times\)3. These results will guide future work towards real-time decoding over embedded platforms. In Table 9, a comparison of the computational load distribution for different blocks of the decoder is shown.