In this paper we review and summarize research results concerning video encoding parallelization, with a primary focus on medium and fine grained methods that operate at block or inner block levels. Taxonomies are illustrated wherever applicable with emphasis to scalability issues. Given the reported results, we turn our attention into the problem of allocating resources (processing cores) to parallel tasks performed by the encoder so as to achieve high speedup. We advocate that a parallelization scheme taking advantage of independently coded areas (e.g., tiles), wavefront parallelism within each area and inner block parallelism at the CTU compression level, can achieve significantly higher parallelization degree compared to standalone methods. An algorithm is then proposed that takes resource allocation decisions at all the aforementioned levels. Both the proposed algorithm and standalone representative approaches from the relevant literature are evaluated in terms of scalability using CTU coding times recorded by CU split parallelism in VTM 6.2. Results show that the potential scalability of the proposed scheme surpasses alternatives.
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