| Thank you for the great answer Nick, that's the best summary I could've hoped for! So in summary:  ⇒ low power, high speed inference on x86 CPU 🡺 Intel Movidius  ⇒ low power, high speed inference non x86 🡺 NV Jetson  ⇒ low power, low speed inference 🡺 RPi and similar  ⇒ high power, high speed inference 🡺 GPU(s) NVidia Jetson is the obvious winner, if there is no viable alternative, however Jetson is quite expensive and therefore I can't go that route. I want to speed up training & inference. eGPUs are more or less affordable, but low power training & inference at medium or low-cost would strike me as a clear winner.
    Sorry for the late answer, nonetheless, even though I didn't get an alternative DSP that offers similar advantages as Movidius, I'm still grateful for your insightful comment. |
HOWEVER, If you are careful, for some models you can get cost benefits by training on cloud CPUs. See http://minimaxir.com/2017/07/cpu-or-gpu/