[Core] Allow verified copy-based KV connectors with expandable segments#158
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…rejection _verify_kv_transfer_compat conservatively rejects every KV connector when PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True is set, because connectors that pin or register KV cache memory (NixlConnector via ibv_reg_mr, MooncakeConnector) break when the CUDA VMM allocator remaps physical pages. Copy-based connectors are not affected: they move KV with CUDA kernels or cudaMemcpy at transfer time, dereferencing virtual addresses on every call, so physical remaps are transparent to them. For those deployments both sanctioned escapes are strictly worse: - Unsetting expandable_segments removes the anti-fragmentation margin, which on unified-memory platforms (e.g. GB10 / DGX Spark) directly causes CUDA OOM at previously working gpu_memory_utilization values. - enable_cumem_allocator routes the weights load through the CuMem pool as well (gpu_worker wraps both tag="weights" and tag="kv_cache"), and tens of GB of cuMemCreate RM sysmem allocations OOM the NVIDIA driver (NVRM: NV_ERR_NO_MEMORY from nv_alloc_system_pages) on unified-memory boards - observed as a full node freeze mid weight-load. Add KVTransferConfig.kv_connector_supports_expandable_segments (default False) so the operator can assert their connector is copy-based and skip the rejection. The default behavior is unchanged and the error message now mentions the opt-out. Signed-off-by: Carlos Molina <carlosmolina0615@gmail.com>
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No actionable comments were generated in the recent review. 🎉 ℹ️ Recent review info⚙️ Run configurationConfiguration used: Organization UI Review profile: CHILL Plan: Pro Plus Run ID: 📒 Files selected for processing (3)
📝 WalkthroughWalkthroughAdds an operator-declared KV connector capability for PyTorch ChangesExpandable Segments KV Compatibility
Estimated code review effort: 3 (Moderate) | ~20 minutes Suggested reviewers: Sequence Diagram(s)sequenceDiagram
participant VllmConfig
participant KVTransferConfig
participant LMCacheConnector
VllmConfig->>KVTransferConfig: Read connector capability flag
KVTransferConfig->>LMCacheConnector: Identify configured connector
VllmConfig->>LMCacheConnector: Allow or reject expandable_segments
🚥 Pre-merge checks | ✅ 5✅ Passed checks (5 passed)
✨ Finishing Touches🧪 Generate unit tests (beta)
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Summary
Backports vLLM PR vllm-project#48243 / commit
81866d82into the local inference lab fork.kv_connector_supports_expandable_segmentsassertion.LMCacheConnectorV1to run withPYTORCH_CUDA_ALLOC_CONF=expandable_segments:True.Scope
This PR intentionally contains only the vLLM-owned configuration change. The DCP gather/scatter, heterogeneous KV packing, DCP-local token validation, and LMCache allocator logging changes belong to the external LMCache package and are not duplicated in vLLM.
Duplicate-work check
No open PR in
local-inference-lab/vllmcovers this change. The corresponding upstream work remains open as vllm-project#48243; this PR is a direct backport for the fork rather than a competing upstream implementation.Validation
.venv/bin/python -m pytest tests/v1/kv_connector/unit/test_config.py -v— 16 passed.venv/bin/pre-commit run --files tests/v1/kv_connector/unit/test_config.py vllm/config/kv_transfer.py vllm/config/vllm.py— all applicable hooks passed, including ruff and mypy.venv/bin/python -m compileall -q tests/v1/kv_connector/unit/test_config.py vllm/config/kv_transfer.py vllm/config/vllm.py— passedgit diff main...HEAD --check— passedModel evaluation is not applicable because this changes startup configuration validation only and does not alter model execution or outputs.
Assistance disclosure
AI assistance was used to review repository ownership, transplant the existing upstream commit, and run validation. The substantive patch is the unchanged upstream commit authored by Carlos Molina.
Summary by CodeRabbit
New Features
expandable_segmentsmemory allocator.expandable_segments:Truewhen explicitly enabled.Bug Fixes