Reduce CP shared-KV request-boundary stalls
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.
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@@ -203,6 +203,8 @@ class Envs:
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SGLANG_FORCE_SHUTDOWN = EnvBool(False)
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SGLANG_DEBUG_MEMORY_POOL = EnvBool(False)
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SGLANG_DEBUG_CP_SHARED_KV = EnvBool(False)
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SGLANG_DEBUG_SORT_NVTX = EnvBool(False)
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SGLANG_DEBUG_MOE_SORT_NVTX = EnvBool(False)
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SGLANG_CP_SHARED_KV_CURRENT_REUSE = EnvBool(False)
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SGLANG_CP_SHARED_KV_USE_TAI_MATERIALIZE = EnvBool(False)
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SGLANG_CP_SHARED_KV_ENABLE_MLA_PREFETCH = EnvBool(False)
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