ON.AI - Faster Jobs. Same GPUs. More Revenue

About this session

Faster job completion turns your committed GPUs and power into more billable capacity — and happier customers. On every multi-tenant, multi-job cluster, unrelated workloads share the same network. Standard infrastructure applies one generic setting to all of them, so every job underutilizes the GPUs and the committed power behind it, and runs slower than it can. I'll show benchmark data across inference, fine-tuning, and training workloads: 2–5x faster job completion once the network becomes job-aware. That speed costs nothing extra — no new hardware, no new software stack, no new power draw. Come by if you run GPU infrastructure, or if you're a customer who wants faster jobs and should be asking your provider for it.