I think that's a fair point. NVIDIA GPUs are co-processors and need a host system, which adds significantly to the cost, power draw and size. You can try to min

I think that's a fair point. NVIDIA GPUs are co-processors and need a host system, which adds significantly to the cost, power draw and size. You can try to minimize this (e.g. by maximizing GPU density in a single server, for example you can apparently get 16 GPUs in a blade server format) but it's definitely always a significant factor. My guess is that NVIDIA sees this problem and will move away from the co-processor model and move towards a System-on-a-Chip design with GPU, ARM CPU, NIC and unified memory in a single package. If Parallella saw large usage in the areas you mention (endpoint devices in control systems, sensor arrays, etc) then the competition could be good for the market and force NVIDIA's hand. Of course Intel is working in a similar direction with Knight's Landing and AMD as well with their APUs (Accelerated Processing Units).