Handle capped SWA admission in allocator path#40027
Handle capped SWA admission in allocator path#40027besquared wants to merge 3 commits intovllm-project:mainfrom
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For hybrid SWA+full-attention models (e.g., Gemma 4), the can_fit_full_sequence admission gate passes full_num_tokens to get_num_blocks_to_allocate for all layer groups, including sliding window groups. Since total_computed_tokens is 0 for new requests, get_num_skipped_tokens returns 0, causing SWA groups to budget ceil(full_num_tokens / block_size) blocks instead of the window- sized amount they actually need. This over-budget throttles concurrent request admission. On Gemma 4 31B with 50 SWA layers (window=1024) and max_num_batched_tokens=8192, each SWA group budgets 1001 blocks instead of 576, causing 4 concurrent 65K-context sessions to be serialized through the gate. Fix: In KVCacheCoordinator.get_num_blocks_to_allocate, cap effective_num_tokens for SlidingWindowManager groups at sliding_window + max_num_batched_tokens. The window term is the steady-state max blocks, and the chunk term accounts for blocks needed during a single prefill chunk before remove_skipped_blocks frees OOW blocks. This matches TensorRT-LLM's getNeededBlocksOneStep. Plumbing: max_num_batched_tokens flows from SchedulerConfig through KVCacheManager and get_kv_cache_coordinator to all coordinator subclasses. Signed-off-by: Jhao-Ting Chen <jhaotingc@nvidia.com> Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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Code Review
This pull request implements Sliding Window Attention (SWA) budget capping in the KV cache allocator to prevent over-allocation. It introduces max_num_batched_tokens across the KV cache management stack and adds a secondary safety check in allocate_slots to ensure the allocator does not fail when requests already hold blocks. Feedback suggests refactoring the allocate_slots method to use a dictionary for shared arguments in get_num_blocks_to_allocate calls, improving maintainability by adhering to the DRY principle.
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Hi @besquared so this resolves the issue you find on 39866? thanks for fixing. |
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Yes the crash doesn't happen with this applied and it's been running gemma4 MoE and dense fine for 12+ hours straight under heavy concurrency with full saturation on my RTX 6K Pro. Current runtime stack on our side: Base:
On top of that:
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Purpose
Follow-up to #39866.
#39866fixes the original head-of-line scheduler stall by capping SWA admission budgeting, but there is still anadmission/allocation mismatch in one edge case:
get_num_blocks_to_allocate()uses the capped SWA budgetValueError: Cannot get 1 free blocks from the poolThis PR keeps the capped SWA admission behavior from
#39866, but adds an uncapped safety check before allocation so this path returnsNonecleanly instead of throwing.Test Plan
Focused unit test: