Hey Lambda ops/infra folks, I’m a Cal Poly student who’s been a customer of yours, and I’m researching something I know you hit: distinguishing “GPU is busy” from "cooling is failing. We validated that computing R_theta (junction temp / power) cleanly separates these two states in real time. Stage 1 data on Colab T4s: clean idle ~1.28 C/W, under load ~0.72 C/W, 78% difference,
reproducible to 1.68% across trials. Building an open-source agent to flag cooling degradation before throttling. Targeting end of June for v0. Real question: when one of your customer’s GPUs runs hot, how do you currently diagnose whether it’s the workload or the cooling path failing? Do you have good tooling for that, or is it a pain point?
Repo / Stage 1 findings: github.com/asomisetty/thermalos
Would love your ops team’s perspective before we ship.