401de0f8ce
Host HiCache reservations were paying token-level free-slot scans when trying to preserve page contiguity. The allocator now keeps a lazy page-extent index so availability checks and contiguous-preferred allocations avoid materializing the full 220GB-equivalent free-slot metadata path. The companion benchmark models steady-state L2 churn near full occupancy, including burn-in and historical node-size effects, so LPF/RDMA descriptor quality can be separated from ETE noise. Constraint: CP HiCache host allocations are page-shaped, but existing callers may still read free_slots directly. Rejected: Sort and scan free_slots on each alloc_contiguous_preferred call | measured ms-level CPU overhead on 220GB-equivalent metadata. Rejected: Remove free_slots compatibility | storage/tests still rely on the public tensor surface. Confidence: medium Scope-risk: moderate Directive: Do not reintroduce per-allocation full free_slots scans on HostKVCache; preserve page-extent metadata or benchmark before changing allocator shape. Tested: Local py_compile for memory_pool_host.py, allocator benchmark, and related tests. Tested: Local test_cp_hicache_allocator_bench.py 10 passed. Tested: Remote g0034 test_hicache_controller_cp.py 67 passed; test_cp_hicache_allocator_bench.py 10 passed. Tested: Remote 220GB-equivalent host_churn benchmark: contiguous path reduced from ms-level to ~30-292us p50 depending on fragmentation. Not-tested: Full CUDA ETE run after allocator change. Not-tested: Production long-run fragmentation behavior under live traffic.
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.