For large bs (production target: bs~10 x ~100k tokens), per-layer granularity does
10x79 = 790 submitTransfer calls + CUDA events + enqueues per forward on the forward
thread. Two overhead cuts:
- Group SGLANG_CP_SHARED_KV_PER_LAYER_GROUP (default 8) consecutive layers into ONE
RDMA submit: ~num_layers/K submits + events + enqueues instead of per-layer; same
bytes (page index lists are identical across layers). on_layer_end is O(1) at
non-boundary layers. The last partial group enqueues via the num_layers boundary;
any misses fall back to one batched sync submit.
- Scheduler hook skips reqs already registered (bs>1 batch-forming re-iterates the
same reqs ~9x -> was rebuilding the CP filter + context every time).
27 unit tests pass incl. grouping-boundary + batched-fallback.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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