Great questions! Slices are a set of TPU chips that share a fast, private inter-chip-interconnect. Unlike the current GPU generation in clouds, the TPUs on different machines can communicate through this private network. Multislice means that we're using a hierarchical network, where there is both inter-chip-interconnect and normal data-center netowrking.
Also, I should point out that a set of machines hosting TPUs is referred to as a "pod", which is not the same thing as a Kubernetes pod (also referenced in this doc).
Kubernetes chose "pod" to represent a set of co-scheduled containers, like a "pod of whales". Other systems like Mesos and Google's Borg https://storage.googleapis.com/pub-tools-public-publication-... use "task" to refer to a single container but didn't have a concept for heterogenous co-scheduled tasks at the time.
Somewhat ironically, it now means TPUs on GKE are confusing because we have TPUs hosts organized into "pods", and "pods" for the software using the TPUs.
A Kubernetes pod using a TPU lands on a host which is part of a slice of a TPU pod.
True. The pod’s monotonic and atomic lifecycle across containers is a significant difference, but you can broadly accomplish similar behaviors with an alloc for sharing resources.
