Ask HN: Reinforcement learning for single, lower end graphic cards?

Re:Ask HN: Reinforcement learning for single, lower end grap... by KMnO4 on Monday July 19, 2021 @10:53AM (#27883289)

Yes. GPUs are extremely good at doing millions of small repetitive calculations, and not great elsewhere.

My capstone project used RL on a Raspberry Pi to train hardware-in-the-loop (essentially when to open and close valves based on sensor input). It was incredibly slow because it couldn’t be parallelized (without buying additional hardware for $500 each). Lots of professors asked why a Raspberry Pi was chosen when we had high end GPUs in the lab, and I had to explain that the Pi was NOT the bottleneck, and in fact stayed idle 95% of the time.

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Re:Ask HN: Reinforcement learning for single, lower end grap... by seg_lol on Monday July 19, 2021 @02:33PM (#27885841)

Would virtual physical simulation have helped in this case? What was the phase lag between valve actuation and the measured signal?

Create a metalearner than can do one-shot learning when it gets access to physical hardware?

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