nemo-mbridge-perf-moe-dispatcher-selectionlisted

# MoE Dispatcher Selection Guide Stable docs: @docs/training/moe-optimization.md Card: @skills/nemo-mbridge-perf-moe-dispatcher-selection/card.yaml ## Quick Decision ### By hardware | Hardware | First choice | Why | |---|---|---| | H100 | DeepEP, if the runtime package is installed | Strong default for cross-node EP on Hopper | | B200 | DeepEP, if the runtime package is installed | Good first choice unless a platform-specific HybridEP path is available | | GB200 / GB300 NVL72 | HybridEP, if the runtime package is installed | Best fit for NVLink-domain-aware dispatch and lower memory pressure | | Unknown or first bring-up | `alltoall` | Easiest path for correctness and debugging | ### By EP degree | EP size | Guidance | |---|---| | Small EP | Dispatcher choice is usually second-order; start with `alltoall` or DeepEP | | Medium EP | DeepEP often becomes worthwhile | | Large EP | HybridEP is usually the best target on NVL72 systems | ## Model-Family Patterns | Workload | Common best path | Notes | |---|---|---| | DSV3 at large scale | HybridEP on GB200 or GB300, DeepEP on H100 | Dispatcher choice matters more as EP and PP both grow | | Qwen3 235B | DeepEP on H100, HybridEP on GB200 | HybridEP usually wins on GB200 and often uses less memory | | Qwen3 30B | DeepEP | Smaller models still benefit, but the absolute gap is smaller | | Qwen3-Next | Close race in BF16, HybridEP stronger in FP8 or memory-tight runs | Good reminder to test, not assume | | MoE VLMs | Start simple,