Yes, I see that they used Unity, so the TPUs themselves couldn’t run the env, but the TPU CPU VM* could run potentially a lot of copies (with that like 300GB of RAM it’s got access to), and that’d be a lot nicer than running remote VMs. At least in Tensorfork, when we try to use TPU pods, a lot of time goes into figuring out correct use of the interconnect & traffic because the on-TPU ops are so optimized by default.
(And regardless of which of those tricks this open-ended paper uses, this is a point well worth knowing about how research could potentially gets way more performance out of a TPU pod than one would expect from knowing TPU usage of old stuff like AlphaStar.)
* advertisement: access to the VM was recently unlocked for non-Google TPU users. It really changes how you treat TPU use!
Yes, I see that they used Unity, so the TPUs themselves couldn’t run the env, but the TPU CPU VM* could run potentially a lot of copies (with that like 300GB of RAM it’s got access to), and that’d be a lot nicer than running remote VMs. At least in Tensorfork, when we try to use TPU pods, a lot of time goes into figuring out correct use of the interconnect & traffic because the on-TPU ops are so optimized by default.
(And regardless of which of those tricks this open-ended paper uses, this is a point well worth knowing about how research could potentially gets way more performance out of a TPU pod than one would expect from knowing TPU usage of old stuff like AlphaStar.)
* advertisement: access to the VM was recently unlocked for non-Google TPU users. It really changes how you treat TPU use!