49eaf9ffde
CP shared KV now avoids the PyTorch sort/search remap for the single-request current-only path by deriving compact rows from page-level inverse mapping. The same change keeps sort NVTX attribution gated and splits high-frequency MoE sort markers behind a separate env var so profiling does not perturb normal runs. Decode-side disaggregation prealloc also avoids rebuilding large token index tensors and records finer allocation timing, while compute-owner allocation/free tests cover the shared-KV page-lane behavior. Constraint: The runtime tree used for validation is the remote /sgl-workspace/sglang-tai mount, which is not itself a Git repository, so these tracked files were synchronized into the local repo before commit. Rejected: Keep torch.sort/searchsorted for current remap | it emits ATen/CCCL radixSortKVInPlace kernels in the attention hot path. Rejected: Enable MoE sort NVTX under the generic sort env | the MoE preprocess sort is too frequent and can make profiling look like a hang. Confidence: medium Scope-risk: moderate Directive: Do not reintroduce token-level torch.sort/searchsorted in CP shared-KV current remap without profiling the attention hot path under Nsight. Tested: Remote container py_compile for modified runtime files; git diff --cached --check. Not-tested: Full multi-node GLM5 PD throughput/profile rerun after the page-inverse current remap.
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.