Ask HN: Robotics engineers – how painful was setting up GPU sim infra?
9 comments
Former ML engineer here who ran IsaacGym and MuJoCo sims in the cloud for 2+ years. The pain is real and very specific:
1. Cold start latency killed iteration loops. Spinning up a GPU VM to test a 10-minute sim run took longer than the sim itself — you'd wait 3-5 min for the instance, run 8 min, tear down. That per-iteration overhead crushes exploration.
2. Idle billing. If you're grid-searching over reward functions, you want to fire 20 parallel runs, collect results, tune, repeat — but most providers bill per-hour so even a 12-minute run costs you a full hour.
3. Physics sim + CUDA dependencies. Custom CUDA kernels (warp sim, etc.) often need specific driver versions. Docker helps but image build/push overhead adds another 5-10 min to the loop.
The "CI for sims" framing (push code → run on GPU automatically) directly addresses #1 and #3. Worth building.
On the infrastructure layer: we built GhostNexus (https://ghostnexus.net) to address #1 and #2 — per-second billing, <30s cold starts on RTX 4090 hardware, Python SDK with 3 lines to submit a job. Might be worth using as the GPU backend if you don't want to manage the infra layer yourself. (Disclaimer: I'm the founder.)
1. Cold start latency killed iteration loops. Spinning up a GPU VM to test a 10-minute sim run took longer than the sim itself — you'd wait 3-5 min for the instance, run 8 min, tear down. That per-iteration overhead crushes exploration.
2. Idle billing. If you're grid-searching over reward functions, you want to fire 20 parallel runs, collect results, tune, repeat — but most providers bill per-hour so even a 12-minute run costs you a full hour.
3. Physics sim + CUDA dependencies. Custom CUDA kernels (warp sim, etc.) often need specific driver versions. Docker helps but image build/push overhead adds another 5-10 min to the loop.
The "CI for sims" framing (push code → run on GPU automatically) directly addresses #1 and #3. Worth building.
On the infrastructure layer: we built GhostNexus (https://ghostnexus.net) to address #1 and #2 — per-second billing, <30s cold starts on RTX 4090 hardware, Python SDK with 3 lines to submit a job. Might be worth using as the GPU backend if you don't want to manage the infra layer yourself. (Disclaimer: I'm the founder.)
This is really interesting, thanks for this insight. Ghost nexus looks awesome, would love to chat some more!
nikhilol(1)
Genuinely trying to understand if this is painful enough to pay to avoid or just annoying for a few weeks and then fine.
(I have a landing page but no product yet, posting to validate before building!)