{
  "kind": "modeled hardware lower bound; not a measurement or fitted curve",
  "beat_steps": 2,
  "model_step_ms": 80,
  "context_steps": 1500,
  "model": "Nemotron VoiceChat; emitted steady-state two-step graph",
  "hardware": {
    "name": "nvidia-h100-sxm-80gb",
    "hbm_bytes_per_second": 3350000000000.0,
    "bf16_flops_per_second": 989000000000000.0,
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    "fp32_flops_per_second": 66900000000000.0,
    "source": "https://www.nvidia.com/en-eu/data-center/h100/"
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  "method": "For each operation, ideal time = max(FLOPs / matching dense compute peak, modeled HBM bytes / HBM peak). Propagate readiness over the operation DAG, preserving serial dependencies and allowing independent branches to overlap. The lower bound is max(the maximum of shared Tensor Core demand (BF16 plus TF32) and FP32 CUDA-core demand, total modeled HBM time, longest dependency-path time). Shared weight traffic is counted per cohort, not multiplied by sessions. This is an optimistic bound under the disclosed traffic and precision model, not a solved attainable schedule.",
  "assumptions": [
    "Dense arithmetic at the emitted precision, no sparsity or precision changes.",
    "Peak full-chip compute and bandwidth; ideal overlap where dependencies permit.",
    "Traffic follows the emitted model inventory; caches, fusion and actual runtime traffic may differ.",
    "No host, launch, barrier, scheduling or load-imbalance overhead.",
    "BF16 and TF32 share Tensor Cores. FP32 CUDA-core and Tensor Core demand are separate resource bounds; ideal overlap between those resources is allowed. Dependencies still use the per-operation readiness calculation."
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