CP shared KV needs HiCache backup to overlap with layer execution without exposing partially copied host state. Split CP backup into reservation, pending radix state, per-layer target/draft D2H submission, and one final ack-driven visibility commit. The all-layer path remains available only as an explicit fallback and now logs a warning when used. Constraint: CP shared KV owner-lane metadata and draft/MTP KV must stay strongly synchronized with target KV. Constraint: Local CUDA tests are disallowed; CUDA verification was run only in the g0034 container. Rejected: Let target layer hooks copy draft KV too | draft may not have stored that layer yet, which can corrupt MTP accept behavior. Rejected: Silent all-layer fallback | it hides performance regressions and makes ETE logs ambiguous. Confidence: medium Scope-risk: broad Directive: Reserved or partially copied host payloads must remain invisible until final ack commits pending_host_backups. Tested: g0034 docker /sgl-workspace/sglang-tai PYTHONPATH=/mnt/beegfs/cjy/tai-kernel/python:python python -m pytest test/registered/unit/managers/test_hicache_controller_cp.py -q -> 49 passed. Tested: g0034 docker /sgl-workspace/sglang-tai PYTHONPATH=/mnt/beegfs/cjy/tai-kernel/python:python python -m pytest test/registered/unit/mem_cache/test_cp_hicache_metadata.py -q -> 58 passed. Tested: g0034 docker /mnt/beegfs/cjy/tai-kernel PYTHONPATH=python python -m pytest tests/nsa_prefill/test_kvcacheio_lf_pf.py -q -> 7 passed. Not-tested: Long-running GLM5 CP+HiCache+MTP ETE throughput and host-pressure soak.
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.