Who-GPU, a simple monitoring tool to view GPU usage across machines

Hacker News

At my university, we have a bunch of GPU machines, but no scheduling system. So you would have to manually SSH into them and check which ones are in use before you start a job. So, I made a CLI to automate that for me. That evolved into a dependency-free webpage as well. It works on Linux, Mac, and Windows (windows needs Git Bash.) If you regularly SSH into machines to check their GPU usage, you are the perfect user! I'd love your feedback.

Visit product View on Hacker NewsSep 16, 2026

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, user · Missing: agents, macos, agent

65%65% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released

59%59% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

50%50% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

30%30% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

17%17% predicted probability of success on BetaList, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Incorrect prediction on native model

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