According to Tom’s Hardware  Intel's video decoding/encoding engines that come built into its CPUs have dominated the market both because they offered leading-edge performance and capabilities and because they were easy to use.

However custom-built application-specific integrated circuits (ASICs) tend to outperform general-purpose hardware because they are designed for one workload only. As such, Google turned to develop its own specialised hardware for video processing tasks for YouTube.

Google had two options for transcoding/encoding content. The first option was Intel's Visual Computing Accelerator (VCA) that packed three Xeon E3 CPUs with built-in Iris Pro P6300/P580 GT4e integrated graphics cores with leading-edge hardware encoders. The second option was to use software encoding and general-purpose Intel Xeon processors.

However the search engine outfit thought that neither of these was power-efficient enough for emerging YouTube workloads. Scaling the number of Xeon CPUs meant increasing the number of servers, which means additional power and data center footprint.

Google's Argos VCU resembles a GPU that always needs an accompanying CPU, so some Intel gear is needed. Instead of stream processors like we see in GPUs, Google's VCU integrates ten H.264/VP9 encoder engines, several decoder cores, four LPDDR4-3200 memory channels (featuring 4x32-bit interfaces), a PCIe interface, a DMA engine, and a small general-purpose core for scheduling purposes.

Google says that its VCU-based machines have seen up to 7x (H.264) and up to 33x (VP9) improvements in performance/TCO compute efficiency compared to Intel Skylake-powered server systems. This improvement accounts for the cost of the VCUs (vs. Intel's CPUs) and three years of operational expenses, which makes VCUs an easy choice for video behemoth YouTube.