laoyao0822andOmX
8571fe0cd9
CP HiCache previously let the target host pool and the draft/MTP host pool each consume the full --hicache-size budget. With EAGLE/MTP enabled this doubled per-rank host allocation and could kill scheduler ranks during startup before Python emitted a traceback. The cache now treats target KV and draft KV as one logical host-cache object: target and draft capacities are computed from one per-rank byte budget, draft may receive more token capacity when its per-token footprint is smaller, and draft attachment remains tied to target residency. Constraint: --hicache-size is a per-rank host budget and must not be multiplied by attaching draft KV. Rejected: Give draft another independent --hicache-size allocation | repeats the observed host OOM failure mode. Rejected: Disable draft HiCache attachment under CP | avoids OOM but breaks target/draft cache-hit consistency for MTP. Confidence: medium Scope-risk: moderate Directive: Keep target and draft KV as one logical HiCache object; do not let draft host allocation consume an independent full hicache-size budget. Tested: python -m py_compile on modified scheduler/cache/test files Tested: remote g0034 container PYTHONPATH=python python -m pytest test/registered/unit/mem_cache/test_cp_hicache_metadata.py -q (45 passed) Not-tested: full multi-rank GLM5 server restart after clearing existing remote router/defunct process state 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.