leavelet
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Peers only ever read the CURRENT pages of a rank's compose output — the prefix comes straight from the IPC-registered KV pool — so the symm region does not need to hold the whole dense buffer (pool-bound ~2.5 GB double-buffered slab). It now holds one round of current pages in merged-span order (extend-cap-bound, ~58-100 MB), and dense buffers become purely rank-local (plain allocations or the optional local arena; COMPOSE_SYMM no longer requires COMPOSE_ARENA). Exchange per compose call: publish my written current pages dense[page] -> staging[slot i] (slot = the page's batch current index, identical on every rank, so peers address each other's staging with no per-batch handshake), cp_symm_barrier, gather peers' staging[writer][slot] -> dense[page] via the existing src!=dst page gather. Reuse safety keeps the parity-half distance-2 argument, now on the staging. Capacity sizing comes from the admission caps (max_total_extend_tokens / max_batch_requests) with a pool-derived fallback and the SYMM_HEAP_MB override; overflow fails fast (batch-logical, hence rank-uniform). Idea credit: laoyao0822's touched-pages-proportional staging (906ecbe5d4), rebound onto our barrier-gated, group-agreed transport. Validated on g0033 8xH200: 151 unit tests; 8-rank GPU byte-exactness vs compose_v2 across 8 layers (arena on and off, parity halves exercised); benchmark path e (real protocol) byte-exact, current-page exchange 0.196 ms vs 0.354 ms compact-AR isolated. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Registered Tests
Tests under this directory are auto-discovered by run_suite.py via CI registration decorators.
Where Should I Put My New Test?
No server / engine launch required
| What you're testing | Directory | Requires |
|---|---|---|
| Component logic in isolation (cache, scheduler, config, parser, etc.) | unit/<module>/ |
CPU or GPU |
| CUDA kernel correctness | kernels/ |
GPU |
Server / engine launch required (E2E)
| What you're testing | Directory | Requires |
|---|---|---|
| Model inference correctness | models/, 4-gpu-models/, 8-gpu-models/ |
GPU |
| Feature-specific (OpenAI API, LoRA, speculative, distributed, VLM, etc.) | openai_server/, lora/, spec/, distributed/, ... |
GPU |
| Benchmarks (performance, accuracy, stress) | benchmark/ |
GPU |
| Platform-specific | amd/, ascend/ |
Vendor GPU |
See unit/README.md for unit test conventions.