Combining the rt-ai Edge Scaler SPE, the OpenPose GPU SPE and iOSEdgeRemote running on an iPad as a camera/display generated some pretty good results, shown in the screen capture above. Full frame rate (30 frames per second) in OpenBose Body mode was obtained running one OpenPoseGPU SPE instance on each of two nodes: Default (equipped with a GTX 1080 ti GPU) and Node110 (equipped with a GTX 1080 GPU). The Scaler SPE divided up the video stream between the two OpenPoseGPU SPEs in order to share the load between the GPUs, performing its usual reassembly and reordering to generate a complete output stream after parallel processing. Latency was not noticeable.
As another experiment, I tried to achieve the same result with just one node, Default, the GTX 1080 ti node. The resulting configuration that ran at the full 30 FPS is shown above. Three OpenPoseGPU SPEs were required to achieve 30 FPS in this case, two topped out at 27 FPS.
In addition, 22 FPS was obtained in OpenPose Body and Face mode, this time using the second node (Node110) for the OpenPoseGPU2 block. Running OpenPoseGPU2 on the Default node along with the other two did not improve performance, presumably because the GPU was saturating.