Re:4000x Speedup in Reinforcement Learning with Jax
by luchris429 on Saturday April 08, 2023 @11:32AM
(#35494267)
Author here! I didn't realize this got posted on HN. While indeed we do get a speedup by putting the environments on the GPU, most of the speedup seems to come from the ability to easily parallelize RL training with Jax.
While there is work on putting RL environments on accelerators, the main speedup from this work comes from also training many RL agents in parallel. This is largely because the neural networks we use in RL are relatively small and thus don't utilize the GPU very efficiently.
While this was always possible to do, Jax makes it way easier because we just need to call `jax.vmap` to get it to work.
While there is work on putting RL environments on accelerators, the main speedup from this work comes from also training many RL agents in parallel. This is largely because the neural networks we use in RL are relatively small and thus don't utilize the GPU very efficiently.
While this was always possible to do, Jax makes it way easier because we just need to call `jax.vmap` to get it to work.