Google today announced that its second- and third-generation Cloud TPU Pods — its scalable cloud-based supercomputers with up to 1,000 of its custom Tensor Processing Units — are now publicly available in beta.
The latest-generation v3 models are especially powerful and are liquid-cooled. Each pod can deliver up to 100 petaFLOPS. As Google notes, that raw computing power puts it within the top 5 supercomputers worldwide, but you need to take that number with a grain of salt given that the TPU pods operate at a far lower numerical precision.
You don’t need to use a full TPU Pod, though. Google also lets developers rent ‘slices’ of these machines. Either way, though, we’re talking about a very powerful machine that can train a standard ResNet-50 image classification model using the ImageNet dataset in two minutes.
The TPU v2 Pods feature up to 512 cores and are a bit slower than the v3 ones, of course. When using 265 TPUs, for example, a v2 Pod will train the ResNet-50 model in 11.3 minutes while a v3 Pod will only take 7.1 minutes. Using a single TPU, that’ll take 302 minutes.
Unsurprisingly, Google argues that Pods are best used when you need to quickly train a model (and theprice isn’t that much of an issue), need higher accuracy using larger datasets with millions of labeled examples, or when you want rapidly prototype new models.
