Sample Factory supports accelerated sampling regime called double-buffered sampling which
can be enabled by setting
--worker_num_splits=2 (default value) and
--num_envs_per_worker to a multiple of 2.
Note that this feature is independent of sync/async or batched/non-batched mode and can be used in any configuration.
Experience collection in RL is normally a sequential process. We can't collect the next observation until we generate an action based on the current observation.
This means that for CPU-based environments we can't use our CPU cores when we're waiting for the inference to finish. This is a waste of resources and it slows down training.
Double-buffered sampling solves this problem by simulating 2*N environments serially in the same process. While we're waiting for the inference to finish on the first N environments, we can already collect observations from the next N environments.
The diagram below shows how this works:
Additionally, take a look at this animation that demonstrates double-buffered sampling: https://www.youtube.com/watch?v=0AyaeLqXQc4
Created: May 9, 2023