41–50 of 95 posts
I wonder if Chinese companies will use (or be allowed to use) TPUs. It seems like a pretty obvious way to have the NSA scoop up any Chinese AI advancements China may want to keep secret.
I wonder which Chinese companies are developing their own processors like TPUs.
The bar graph seems a little whacky. It groups the TPU (which can only do FP16) with the FP32 results from the GPUs, then puts the FP16 GPU results off to the side even though that's much closer to what the TPU is doing. Impressive results regardless though; quite a bit faster than V100 than the paper specs would suggest.
Disclosure: I work on Google Cloud. While not perfect, I want to commend the RiseML folks for doing not only an “just out of the box” run in both regular and fp16 mode (for V100), but also adding their own LSTM experiment to the mix. We need third-party benchmarks whenever new hardware or software are being sold by vendors (reminder: I benefit from you buying Google Cloud!). I hope the authors are able to collect som…
It makes any benchmarks become Google-cloud benchmarks, right?
Edit: I am complaining a bit about the lack of availability but there's also a real point here. If there's no source for TPUs outside of Google, Google Cloud competes only with other cloud providers and with owning physical GPUs - long term, it has no incentive to be anything but little bit more efficient than these however much it's price for producing TPUs declines.
Earlier quoted context omitted.
It's interesting to me that the assumption here is that government actors are interested in this as opposed to the companies hosting them.
Oh, I totally agree with you there. It's just I consider Google a government actor too.
[Edited] The top line results focus on comparing four TPUs in a rack node (which marketing cleverly named “one cloud TPU”), running ~16 bit mixed precision, to one GPU (out of 8 in a rack node), also capable of 16 bit or mixed precision, but handicapped to 32 bit IEEE 754. That is a misleading comparison. Images/$ are obviously more directly comparable, but again the emphasized comparisons are at different precision.…
Disclosure: I work on Google Cloud. While not perfect, I want to commend the RiseML folks for doing not only an “just out of the box” run in both regular and fp16 mode (for V100), but also adding their own LSTM experiment to the mix. We need third-party benchmarks whenever new hardware or software are being sold by vendors (reminder: I benefit from you buying Google Cloud!). I hope the authors are able to collect som…
So this is a chip that no one outside of Google is going to be able to get a physical copy of ever? It makes any benchmarks become Google-cloud benchmarks, right? Edit: I am complaining a bit about the lack of availability but there's also a real point here. If there's no source for TPUs outside of Google, Google Cloud competes only with other cloud providers and with owning physical GPUs - long term, it has no incen…
[Edited] The top line results focus on comparing four TPUs in a rack node (which marketing cleverly named “one cloud TPU”), running ~16 bit mixed precision, to one GPU (out of 8 in a rack node), also capable of 16 bit or mixed precision, but handicapped to 32 bit IEEE 754. That is a misleading comparison. Images/$ are obviously more directly comparable, but again the emphasized comparisons are at different precision.…
It's all about performance per dollar.
Disclosure: I work on Google Cloud. While not perfect, I want to commend the RiseML folks for doing not only an “just out of the box” run in both regular and fp16 mode (for V100), but also adding their own LSTM experiment to the mix. We need third-party benchmarks whenever new hardware or software are being sold by vendors (reminder: I benefit from you buying Google Cloud!). I hope the authors are able to collect som…
So this is a chip that no one outside of Google is going to be able to get a physical copy of ever? It makes any benchmarks become Google-cloud benchmarks, right? Edit: I am complaining a bit about the lack of availability but there's also a real point here. If there's no source for TPUs outside of Google, Google Cloud competes only with other cloud providers and with owning physical GPUs - long term, it has no incen…
(I'm saying this with my CMU hat, not my Google hat.)
Earlier quoted context omitted.
So this is a chip that no one outside of Google is going to be able to get a physical copy of ever? It makes any benchmarks become Google-cloud benchmarks, right? Edit: I am complaining a bit about the lack of availability but there's also a real point here. If there's no source for TPUs outside of Google, Google Cloud competes only with other cloud providers and with owning physical GPUs - long term, it has no incen…
I thought they were going to provide to other cloud providers? I’m also guessing if you’re willing to purchase a lot of them then they’re willing to talk...
It may be that the other cloud providers would then sell them to those individuals. Indeed, the job of entities called "distributors" to buy big lots from manufacturers and break them up.
And of course, I don't know what the point of (apparently) keeping them out of the average person's hand would be.