

Customizability of parallelism, failure tolerance, and many other settings;


A large selection of state-of-the-art optimization algorithms;


Saving in-progress experiments (to a SQL DB or json) and resuming an experiment from storage;


Easy extensibility to new backends for running trial evaluations remotely.


The following illustration from the Ax scheduler tutorial summarizes how the scheduler interacts with any external system used to run trial evaluations:




To run automated NAS with the Scheduler, the main things we need to do are: