25The cluster dashboard says 90% allocated and 30% utilized. What is happening, how do you prove it, and what policy fixes it?▼hardNewOpenAIAnthropicMeta4 replies◆ premiumAllocated means a scheduler handed the GPU out; utilized means it did work. A 60-point gap is jobs holding GPUs they do not use: idle notebooks, placeholder jobs, a loader-bound run at 20% tensor-active. The three metrics that separate the causes, the per-tenant table that names them, and the policies that close it.Open full answer →
27Design a notebook platform for 300 researchers on 64 GPUs. How do you share, reclaim and account for the GPUs?▼mediumNewDatabricksGoogle4 replies◆ premiumA notebook holds a GPU for eight hours and uses it for twenty minutes, which is what sharing is for and what makes it hard. The sharing mode to pick and the one to refuse across users, the idle-reclaim loop that keeps sessions alive without holding hardware, the quota arithmetic, and how many GPUs 300 users need.Open full answer →