This feature provides support for leveraging Graphics Processing Units (GPUs) for increasing transcoding capacity of SBC SWe instances, and the ability to instantiate the same on an OpenStack cloud. GPU acceleration significantly increases transcoding capacity of virtual instances, which otherwise would have a limited scale. In many cases GPU-accelerated solution perform better than specialized DSP hardware-based solutions. GPU-based solutions have the following benefits:
G.722 Silence Suppression is not supported with GPU transcoding.
GPU acceleration is currently supported on SBC SWe cloud-based T-SBC instances on OpenStack (Newton and above). T-SBC is a component in the Distributed SBC architecture that provides transcoding service.
GPU devices are attached to SBC cloud instances through PCIe pass-through – a single GPU device can be used by only one instance at a time. The process of enabling PCIe pass-through in OpenStack is described in Configuring SBC SWe Cloud for GPU Transcoding. For performance considerations, NUMA locality of devices should be ensured.
NVIDIA GRID is not supported.
NVIDIA V100(PCIe), 16 GB variant only
In addition, G.711 is supported for GPU instances, but only when G.711 is being transcoded to a non-G.711 codec. You cannot currently configure transcoding from G.711 to G.711 on GPU instances. The codec modes and packetization times for the supported codecs are the same as those that apply to SBC SWe in the tables on the Audio Codecs page.
The GPU transcoding solution currently does not support more than one non-G711 transcodable codec per leg on a trunk group. Therefore when configuring Packet Service Profiles, do not configure multiple non-G711 codecs on a single leg (This Leg/Other Leg parameters) when specifying the Codecs Allowed For Transcoding within Packet To Packet Control. Refer to Packet Service Profile - CLI or Packet To Packet Control - Codecs Allowed For Transcoding (EMA).
While GPU-based T-SBCs offer marked increase in scale when compared to CPU based T-SBCs, there are some caveats with the GPU solution that are highlighted in the following table.