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Comment by fiatmoney | Hacker News Reader

I'm guessing that the performance / watt claims are heavily predicated on relatively low throughput, kind of similar to ARM vs Intel CPUs - particularly because they're only powering it & supplying bandwidth via what looks like a 1X PCIE slot.

IOW, taking their claims at face value, a Nvidia card or Xeon Phi would be expected to smoke one of these, although you might be able to run N of these in the same power envelope.

But those bandwidth & throughput / card limitations would make certain classes of algorithms not really worthwhile to run on these.

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> IOW, taking their claims at face value, a Nvidia card or Xeon Phi would be expected to smoke one of these, although you might be able to run N of these in the same power envelope.

That seems unlikely, right? GPGPU software beating an ASIC? I guess it depends on just how abstract and adaptable the TPU IC is. Sounds like they use a custom number representation -- if they can squeeze it into less than half precision (IEEE FP16) then it would be super hard for a Phi or GPU to beat it.

But ultimately it all comes down to specific applications' bottlenecks. If they don't have to go off-card ever and their workset fits into the on-die memory, then they'd have no real advantage by using a PCIe GPU with GDDRx on it.

> I'm guessing that the performance / watt claims are heavily predicated on relatively low throughput, kind of similar to ARM vs Intel CPUs - particularly because they're only powering it & supplying bandwidth via what looks like a 1X PCIE slot.

Agreed. Also tells you that they don't need to communicate with the CPU much, given that it only has a PCIE. Reminds me of Knights Ferry, in this respect.

> a Nvidia card or Xeon Phi would be expected to smoke one of these

Will be very interesting to see some head-to-head benchmarks between these guys (on tensorflow and other libraries) in the next few months. Especially as Knights Landing starts to appear, and the new Nvidia card.

I am so happy that Nvidia got a real competitor in the ML hardware market. Maybe now they will be two times more creative.

There are 8 high-speed serial links on the front side of that board and probably 8 on the back. That's quite a bit of bandwidth.

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