dispatch_copy_mdspan.cuh entire design:
1. Check is_exhaustive() + have_same_strides() (layout compatibility)
2. Fast path: if contiguous, use DeviceTransform (1D memcpy-like kernel)
3. Slow path: if non-contiguous, use DeviceFor::for_each_in_extents
Translation to MoE segment loop:
After sorting tokens by expert_id, tokens routed to the same expert
often have consecutive original indices. When they do, hidden_states
slice is zero-copy (view) vs fancy indexing (allocates new tensor).
Check: tok_ids_seg[-1] == tok_ids_seg[0] + n - 1 (contiguous range)
Fast: hidden_states[first:first+n] (zero-copy slice)
Slow: hidden_states[tok_ids_seg] (gather with copy)
CCCL source: cub/cub/device/dispatch/dispatch_copy_mdspan.cuh
Maps to: qwen3_6_scripts/qwen3_5.py (_pure_pytorch_experts)
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