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You do not want to be dependent on Nvidia for your own stuff is why Google has to do the TPUs. It is like how they ported to Power for their stuff if needed.
by jacksmith21006 8y ago
You do not want to be dependent on Nvidia for your own stuff is why Google has to do the TPUs.
It is like how they ported to Power for their stuff if needed.
Look at the shortage of late with Nvidia. Google does not have to deal with it.
But also I suspect they could not do WaveNet without their own silicon as the cost would be prohibitive. Using a NN for speech and competing against traditional approaches and have a competitive price is going to require really efficient silicon.
- shaklee3 8y agoWhat shortage? You can't make statements like that with no basis in reality. The V100 is not suffering from any shortage.
- jacksmith21006 8y ago"Looking to nab Nvidia's GeForce chips? You need cash and patience GPU shortage equals four-month wait time for buyers" https://www.theregister.co.uk/2018/03/30/nvidia_geforce_chips_crypto_miner_induced_shortage/ https://www.theregister.co.uk/2018/03/30/nvidia_geforce_chip... But you are missing my point. Google is not dependent on Nvidia. Really does not look like Nvidia could do what they need anyway. Doing their new text to speech on Nvidia I would not expect to have a price point to make viable.
- shaklee3 8y agoSo let me get this straight. You are saying Nvidia is having a massive shortage of parts, while ignoring that both AWS and GCP offer GPU instances that you can get any time. Not only that, the article you reference is about Geforce GPUs, which is not a data center GPU. You are comparing apples and oranges. Please show me an article where there's a shortage of Tesla cards.
- jacksmith21006 8y agoIt is about being dependent on someone else for something that is critical to you. But really now it is just Nvidia does not have the ability to meet Google's needs. I am not aware of anything from Nvidia that could do 16k cycles through a NN in real-time at a cost that you could roll out at scale. Google priced WaveNet competitively to the old way of doing. You can only do that with a very low cost for computation and the power required which Nvidia could not match with the TPU 1.0 let alone now they have the 3.0.