7284a469a2
CP shared-KV bs>1 cache-hit loads already merge request load ops, but the host pool still rebuilt layer-invariant mapping work from the same host/device indices. Introduce a PreparedLoadDescriptor lifecycle around begin/end load, wire MLA KV and NSA index H2D loads through tai-kernel prepared submit when available, and add timing hooks plus regression coverage for descriptor reuse and explicit fallback logging. Record the P4/P6b design and benchmark results in the advanced feature notes. Constraint: Radix residency and allocator decisions remain synchronous; only the data-transfer descriptor is prepared for per-layer async submit. Constraint: Production fast path must not silently fall back when tai prepared H2D support is missing. Rejected: Cross-batch descriptor reuse | descriptor lifetime and tensor ownership are only safe within one load operation. Rejected: Change L2->L1 scheduling to layer-ahead prefetch in this commit | that is a separate lifecycle change after descriptor reuse is stable. Confidence: medium Scope-risk: moderate Directive: Keep LayerDoneCounter per-layer readiness semantics; do not replace with all-layer waits. Tested: python -m py_compile python/sglang/srt/mem_cache/memory_pool_host.py python/sglang/srt/managers/cache_controller.py Tested: Remote g0034:cjy-glm5-new PYTHONPATH=python python -m pytest -q test/registered/unit/managers/test_hicache_controller_cp.py (88 passed) Tested: Remote tai-kernel prepared descriptor CUDA test (6 passed) and P4 benchmark full matrix (90 rows) Not-tested: ETE replay/GSM8K cache-hit correctness after this commit Not-tested: Layer-ahead L2->L1 prefetch scheduling Co-authored-by: OmX <omx@oh-my-codex.dev>
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.