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I wouldn't be so sure. Edge TPUs could be the exact same architecture than Google Cloud TPUs, but as you need less computation power for inferring than training
by antpls 7y ago
I wouldn't be so sure. Edge TPUs could be the exact same architecture than Google Cloud TPUs, but as you need less computation power for inferring than training, they have simply less transistors on the die and could be underclocked.
In other words, Cloud TPUs could be the same architecture than Edge TPUs but scaled to an higher frequency and more packed.
I guess we need sources to confirm.
- modeless 7y agoEdge TPUs support 8 bit integer math only. Training is floating point. That's not a small change. https://coral.withgoogle.com/docs/edgetpu/models-intro/#model-requirements https://coral.withgoogle.com/docs/edgetpu/models-intro/#mode...
- londons_explore 7y agoTraining is currently done in floating point math, whereas inference can be done fixed point without much loss of performance. Fixed point is ~10x cheaper in terms of power and silicon area for equal performance. Also, training requires a lot more RAM per unit of compute, since it needs to store all past layer activations, whereas for inference, that is unnecessary. As far as I know, no player who has developed dedicated ML hardware (as opposed to using GPU's) uses the same hardware for both inference and training.