[D] Pytorch FSDP is pipeline parallelism right?

edit: To be clear I'm interested in how FSDP deals with models being too big for one GPU (the fact that Data Parallelism is used is not what I want to discuss).

I got to this understanding after reading the [FSDP paper](https://arxiv.org/abs/2304.11277):

> 1. Perform computations with parameter shards and communicate activations accordingly. [...]
> 2. Perform the same computation as local training by communicating parameter on-demand before computations.
Since parameter communications do not have any data dependency on preceding …

big clear computation data deals discuss edit gpu machinelearning pipeline pytorch training