NYDUX is an AI Infrastructure Intelligence company focused on one problem:

Most GenAI systems in production are wasting 30–60% of their GPU compute.

Not because of hardware — but because of hidden system-level inefficiencies:
NCCL misconfiguration, scaling breakdowns, memory fragmentation, and communication overhead that never shows up in standard metrics.

We identify exactly where that loss happens.

Our 5-day GPU Cluster Diagnostic breaks down:
• MFU (real utilization vs theoretical)
• Step-time (compute vs communication vs I/O)
• NCCL configuration and topology mismatch
• Scaling inefficiencies across multi-node clusters

This is designed for platform and ML infrastructure teams running real workloads — where performance, predictability, and cost matter.

Typical outcome:
• 30–60% efficiency gaps identified
• $100K–$600K annual compute waste uncovered
• Clear, actionable fixes — not generic advice

If your cluster is below 40% MFU, you’re already losing money.

🌐 https://nydux.ai/diagnostic

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