Why isnt there more investments into semi-synchronous training - is it that the convergence is iffy ? Also, it would be great to refactor this code into a typed language, so it is easier to reason about and maintain.
Historically it's been limited to areas like federated learning for low power/low network training but with the massive increase in number of GPUs it's becoming relevant even for training in datacenters.
It is another variable ML researchers have to tune so does add some complexity and I expect most folks just aren't familiar with it yet.
On "typed language": all of torchft is typed! The coordination/quorum layers are written in Rust w/ GRPC and the front-end is typed Python with Pyre since it has to interact with PyTorch and model code.
[1] https://github.com/pytorch-labs/monarch/issues/175#issuecomm...