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gpu-instance-fingerprint

Fingerprint the exact GPU you're running on, even among identical GPUs, from the order its atomic adds land in. 99.1% accuracy, survives reboots, can't be faked, and a default torch.index_add_ call leaks it.

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GITHUB · launched Oct 30, 2026 · 29 upvotes (top 51%) · 0 views

Niche: hardware monitoring and diagnostic tools · 115 launches, 11 in the last 7 days ▼ -31% · Explore this niche →

Category and tags

  • Security
  • Developer
  • Not AI
  • cuda
  • cupy
  • device-fingerprinting
  • fingerprinting
  • floating-point
  • gpu
  • +6 more

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Could you build this?

No The core contribution is a novel research technique for identifying individual GPUs from atomic operation ordering, which requires original GPU-architecture research to make robust.

What it would actually take: Reproducing the basic effect is simple, but a reliable version needs an understanding of GPU memory-ordering and scheduling behavior, careful statistical evaluation across many identical devices, and robustness testing across drivers and containers. This is a research-level task for GPU systems researchers.

Competitors

Other products that read as similar to this one : 102 launches clear the similarity bar, closest 8 shown.

Attention rank: #48 of 103 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 318 days after the earliest competitor.

The niche, labels, vibe code rating and competitor comparison on this page are analysis by Nicheloom. If you use them, please credit nicheloom.com. How you may use our data.