Decode DP dispatch was collapsing onto a few ranks because the controller only randomizes among exact minimum load pairs. The load snapshot undercounted decode handoff work: pending prefill-info requests were absent, and DecodeRequest wrappers in prealloc/transfer queues were skipped because their rid lives on .req. This makes scheduler load accounting unwrap DecodeRequest items and include pending decode requests, so TOTAL_TOKENS sees queued handoff backlog instead of repeatedly treating busy ranks as empty. Constraint: Do not mask imbalance with synthetic per-request token penalties; dispatch should be driven by accurate observed load. Rejected: Add req*4000 or other queue penalties | heuristic, workload-dependent, and hides the accounting bug. Confidence: medium Scope-risk: moderate Directive: Any new decode handoff queue must be included in get_load() or DP routing can regress to stale/min-load collapse. Tested: Remote cjy-glm5-new: PYTHONPATH=python python -m pytest -q test/registered/unit/observability/test_scheduler_metrics_load.py test/registered/unit/managers/test_prefill_adder.py -> 27 passed. Not-tested: Fresh decode ETE distribution after service restart.
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.