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[TRTLLM-16186][feat] Lend KV cache pages and recurrent state in place - #20534
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Attention assignment inactive Checked 2026-10-22T15:48:02.684836+00:00. The changed files no longer require There is no outstanding attention team request. Previous attention decision (inactive history)@farazkh80, could you help to review this PR as trt-llm-torch-attention-devs? Thanks~ <details> <summary>Assignment explanation</summary> <table> <tr><th>Components</th><td>runtime/kv-cache/lifecycle (40%); runtime/kv-cache/layout-io (35%); runtime/recurrent-state (5%); runtime/sparse-cache (5%); integration/attention-tests (15%)</td></tr> <tr><th>Tags</th><td>features:paged-kv (100%)</td></tr> <tr><th>PR effort</th><td>13 points — The visible API additions and shared layout/lifecycle integration support a feature classification. Reviewing the coupled layout compatibility, lease ownership, commit locking, fetch resumption and recurrent-state contracts warrants substantial architectural reasoning. The 13-point estimate remains provisional because most implementations are hidden.</td></tr> <tr><th>Importance</th><td>Important — The layout version changes from 2 to 3, host-tier tests adopt MemoryKind/RowSelection, and KV and recurrent managers gain lender-hook imports. Together with the declared block-lock and safe-resume responsibilities, this indicates a broad cache-sharing interface and sensitive lifetime/correctness change.</td></tr> <tr><th>Affinity (0–1)</th><td>0.541 component/tag match; 0.406 after PIC preference</td></tr> <tr><th>Outstanding points at selection</th><td>19 → 32 (+13)</td></tr> <tr><th>Points already reserved on this PR</th><td>0</td></tr> <tr><th>Effective weight</th><td>1</td></tr> <tr><th>Completed review points (preceding 168 hours)</th><td>63</td></tr> <tr><th>Combined points after assignment</th><td>95</td></tr> <tr><th>Demand-derived target</th><td>85.25 points (soft share)</td></tr> <tr><th>Additional fair share before assignment</th><td>3.25 points</td></tr> <tr><th>Share explanation</th><td>Whole PR / qualification or coverage constraint exceeds a soft share; assignment is allowed.</td></tr> <tr><th>Selection rule</th><td>affinity with 0.3-share guard</td></tr> <tr><th>Assignment scope (farazkh80)</th><td>all</td></tr> </table> <p>Affinity and workload are snapshots at selection, not live counters. Existing reservations on this PR are counted once.</p> </details> |
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WalkthroughThe pull request adds immutable page-layout descriptors and changes KV-cache lending to support host and device leases. It adds page locks, fetch delivery tracking, attention read-window metadata, and lock-aware cache-manager and scheduler behavior. ChangesKV-cache lending and page lifecycle
Priority: Estimated code review effort: 5 (Critical) | ~120 minutes Suggested reviewers: Merge Risk:
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| Check name | Status | Explanation |
|---|---|---|
| Title check |  |
The title clearly identifies the feature: in-place lending of KV-cache pages and recurrent state. It uses the required ticket and feature format. |
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Check skipped because no linked issues were found for this pull request. |
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The description clearly explains the purpose, main changes, compatibility considerations, CI status, and validation results. It provides substantial test coverage details. It does not include the temp… |
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Actionable comments posted: 2
- 🪄 Fix comments: Fix CodeRabbit comments on this PR
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Inline comments:
Review comments at @tensorrt_llm/_torch/pyexecutor/kv_cache/_lender_hooks.py:
- Around line 237-243: Update scheduler_holds_page_locks to safely handle draft
managers that do not implement _holds_page_locks: retrieve the draft method
defensively and invoke it only when callable, while preserving the primary
manager check and returning false when no compatible draft method exists.
Review comments at
@tensorrt_llm/_torch/pyexecutor/kv_cache/kv_cache_manager_v2.py:
- Around line 4228-4231: Update the read-window calculation around the
layer-grouping return expression so every declared window is treated as
effective only when positive and is clamped to kept; use kept for None or
non-positive declarations. Preserve taking the maximum across the group, and add
a regression test in test_layout_identity.py covering max_attention_window 256
with declared attention_read_windows 4096, asserting derive_layout succeeds and
read_window equals kept_window.
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📒 Files selected for processing: 56
tensorrt_llm/_torch/attention/backends/fp4_mla/cache_manager.pytensorrt_llm/_torch/attention/backends/sparse/csa2/cache_manager.pytensorrt_llm/_torch/attention/backends/sparse/deepseek_v4/cache_manager.pytensorrt_llm/_torch/attention/backends/sparse/minimax_m3/cache_manager.pytensorrt_llm/_torch/attention/backends/sparse/qsa/cache_manager.pytensorrt_llm/_torch/disaggregation/base/memory.pytensorrt_llm/_torch/disaggregation/resource/page.pytensorrt_llm/_torch/pyexecutor/_util.pytensorrt_llm/_torch/pyexecutor/kv_cache/_lender_hooks.pytensorrt_llm/_torch/pyexecutor/kv_cache/kv_cache_manager_v2.pytensorrt_llm/_torch/pyexecutor/kv_cache/mamba_cache_manager.pytensorrt_llm/_torch/pyexecutor/kv_cache/page_layout.pytensorrt_llm/_torch/pyexecutor/kv_cache/sharing/__init__.pytensorrt_llm/_torch/pyexecutor/kv_cache/sharing/_fetch_ledger.pytensorrt_llm/_torch/pyexecutor/kv_cache/sharing/_identity.pytensorrt_llm/_torch/pyexecutor/kv_cache/sharing/_layout.pytensorrt_llm/_torch/pyexecutor/kv_cache/sharing/_lender.pytensorrt_llm/_torch/pyexecutor/kv_cache/sharing/_manager.pytensorrt_llm/_torch/pyexecutor/kv_cache/sharing/_page_locks.pytensorrt_llm/_torch/pyexecutor/kv_cache/sharing/_ranges.pytensorrt_llm/_torch/pyexecutor/kv_cache/sharing/_slots.pytensorrt_llm/_torch/pyexecutor/kv_cache/sharing/_types.pytensorrt_llm/_torch/pyexecutor/py_executor.pytensorrt_llm/_torch/pyexecutor/scheduler/scheduler_v2.pytests/unittest/_torch/executor/kv_cache/sharing/conftest.pytests/unittest/_torch/executor/kv_cache/sharing/test_generation_lender_hooks.pytests/unittest/_torch/executor/kv_cache/sharing/test_host_tier.pytests/unittest/_torch/executor/kv_cache/sharing/test_in_place_leases.pytests/unittest/_torch/executor/kv_cache/sharing/test_in_place_lending.pytests/unittest/_torch/executor/kv_cache/sharing/test_in_place_omitted_buffers.pytests/unittest/_torch/executor/kv_cache/sharing/test_in_place_rows.pytests/unittest/_torch/executor/kv_cache/sharing/test_in_place_running.pytests/unittest/_torch/executor/kv_cache/sharing/test_in_place_running_rules.pytests/unittest/_torch/executor/kv_cache/sharing/test_in_place_state_and_helix.pytests/unittest/_torch/executor/kv_cache/sharing/test_layout_identity.pytests/unittest/_torch/executor/kv_cache/sharing/test_layout_matches_native_page_table.pytests/unittest/_torch/executor/kv_cache/sharing/test_layout_public.pytests/unittest/_torch/executor/kv_cache/sharing/test_lender_fast_paths.pytests/unittest/_torch/executor/kv_cache/sharing/test_page_lock_hooks.pytests/unittest/_torch/executor/kv_cache/sharing/test_page_locks.pytests/unittest/_torch/executor/kv_cache/sharing/test_pipeline_stages.pytests/unittest/_torch/executor/kv_cache/sharing/test_public_surface.pytests/unittest/_torch/executor/kv_cache/sharing/test_reuse_prefixes.pytests/unittest/_torch/executor/kv_cache/sharing/test_slots.pytests/unittest/_torch/executor/kv_cache/sharing/test_staging_lender.pytests/unittest/_torch/executor/kv_cache/sharing/test_window_slack.pytests/unittest/_torch/executor/kv_cache/test_kv_cache_manager_v2_helix_superblock.pytests/unittest/_torch/executor/kv_cache/test_kv_cache_v2_scheduler.pytests/unittest/_torch/executor/kv_cache/test_kv_pool_rebalance.pytests/unittest/_torch/executor/kv_cache/test_spec_recompute_tail.pytests/unittest/_torch/executor/test_kv_connector_v2_prefix.pytests/unittest/_torch/executor/test_kv_connector_v2_prefix_real_manager.pytests/unittest/_torch/executor/test_layer_type_attention_windows.pytests/unittest/_torch/executor/test_multimodal_scheduler.pytests/unittest/_torch/executor/test_py_executor.pytests/unittest/_torch/multi_gpu/test_kv_pool_rebalance_tp.py
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Took the first review pass and left 2 inline comments. Will take another review pass once the existing comments are addressed.
Btw, at 8b35ddc, the generation-hook tests fail because their fixtures lack _inflight_draft_lens. The capacity-only fixture also lacks max_attention_window. Please update these fixtures, then rerun the affected tests and full CI.
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Keeping @farazkh80 as the trt-llm-torch-attention-devs reviewer based on their existing review activity on this PR. This confirms existing ownership; it does not request another review or add review points. Why this reviewer is retainedEvidence: inline review comment at 2026-10-22T12:46:24Z. The bot keeps the first eligible attention reviewer who started reviewing. Current target-branch CODEOWNERS includes attention-owned changes in this PR. |
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Signed-off-by: Shixiaowei02 <39303645+Shixiaowei02@users.noreply.github.com>
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PR_Github #81399 [ run ] triggered by Bot. Commit: |
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[by Claude Code] @eopXD Could you review this PR? Thanks! |
Summary
Extend the V2 KV-cache lender with direct access to device KV pages and recurrent state alongside host staging. Transfer integrations borrow native storage while the manager owns its lifetime; row-based leases describe layout, delivery, and safe resume bounds.
Main changes
PageLayoutwith buffers, memory regions, model-layer identities, attention windows, and replica ranks. HOST supports NAMED objects; DEVICE supports NAMED and ALL selections.Rebase and compatibility
mainatb7b797a3aas one signed-off commit. Preserve main's prefix-wait snapshot cleanup alongside lender-held pool lifetime, and initialize both scheduler capabilities in the conflicted multimodal test fixture.a6fd0e1b6byte for byte; both merge orders are conflict-free. Blob consumes the samepage_ordinalsand pairedslots/region_indicescontract, preserving multi-region payload order and destination validation.The C++ library and the CSA2/DeepSeek-V4 cache-manager implementations have no changes in this PR. Transfer backends own byte movement and rank coordination.
CI follow-up
CI #66781 tested
dbc801526: 101,423 passed, with two failing tests plus one wrapper failure.cuMemCreateOOM), before the current model's KV manager was created. Other PRs reproduce the same failure. Its MPI workers had been reused from an earlier R1 MTP test; the passing comparison run followed a different R1 case. Mark this test methodprivate_mpi_sessionto drain cached pools and use fresh workers, retaining all original parameters and accuracy checks. An eight-GPU rerun is still needed to confirm the OOM outcome.Validation
private_mpi_session.679936e08), whose native/build inputs match this checkout. Its 2,101 Python files, 83 native libraries, and 13,801 RECORD entries were verified, followed by a clean B200 install and binding import smoke test.