CPU MICROARCHITECTURAL PERFORMANCE ANALYSIS OF SVT-AV1 ENCODER

Advances in algorithms and the CPU architecture have driven the development of more sophisticated video compression technology, providing superior compression efficiency. With growing demand for ultra-high definition video resolutions and upcoming immersive media applications, new video codecs like AV1, keep introducing enhanced coding tools. However, these enhancements need more computation footprint and support for additional complex dataflow handling. Thus, it is important to understand the behavior of these encoding tools on latest processor architectures to pave path for software/hardware acceleration opportunities. In this work, we investigate the large runtimes taken by AV1 encoding workloads and decipher it through microarchitectural performance evaluation on vbench, a publicly available cloud video benchmark suite. We also present methodology to encode multiple streams in parallel with minimal to no impact on the overall runtime. For certain encoding options we observe a drop of 8%-22% in runtime.