[pull] main from NVIDIA:main

.github/workflows/blossom-ci.yml

@@ -133,6 +133,7 @@ jobs:
         "hijkzzz",
         "hlu1",
         "hnover-nv",
+        "Hudayday",
         "HuiGao-NV",
         "hvagadia",
         "hypdeb",

cpp/include/tensorrt_llm/batch_manager/kvCacheManager.h

@@ -393,10 +393,7 @@ class KVCacheBlock : public std::enable_shared_from_this<KVCacheBlock>
     static BlockPtr createPlaceholder(IdType blockId, SizeType32 windowSize);
 
     void detachDescendantsFromLookupTree();
-    //! \brief Detach all placeholder blocks in the previous-block chain from the lookup tree.
-    //! \details Walks upward via getPrevBlock() and calls detachFromLookupNode() on each
-    //! block that is a placeholder. Stops at the root (kCachedBlocksRootId).
-    void detachPreviousPlaceholdersFromLookupTree() const;
+
     void freeBlockAndAllDescendants();
 
     //! \brief Find block matching blockKey. If allowPartial is true, the returned block may match only a prefix of
@@ -630,7 +627,7 @@ class GenerationRequest
         TLLM_CHECK_WITH_INFO(currentPrepopulatedPromptLen <= mCurrentPrepopulatedPromptLen,
             "currentPrepopulatedPromptLen must be updated non-increasingly due to the "
             "assumption that smaller window sizes have shorter or equal"
-            "currentPrepopulatedPromptLen in WindowSizeManager::loadOrAllocateBlocks.");
+            " currentPrepopulatedPromptLen during multi-window batch allocation.");
         mCurrentPrepopulatedPromptLen = currentPrepopulatedPromptLen;
     }
 
@@ -785,11 +782,6 @@ class WindowBlockManager
 
     void startScheduling();
 
-    //! \brief Assign blocks for new sequence
-    //! \return The number of tokens that were matched/prepopulated from cache (prepopulatedPromptLen)
-    [[nodiscard]] SizeType32 addSequence(GenerationRequest& sequence, SizeType32 inputLength,
-        SizeType32 numContextBlocks, LlmRequest& llmRequest, bool isEnableBlockReuse);
-
     //! \brief Per-request block allocation statistics from batch addSequence.
     struct BatchSeqStats
     {
@@ -1158,16 +1150,6 @@ class WindowBlockManager
     //! \brief Add single block to all beams of sequence.
     void addBlockToAllBeams(BlockPtr const& block, GenerationRequest& sequence);
 
-    //! \brief Try to load blocks from cache. Allocate new blocks if necessary.
-    //! \param blockKeys Key of each block.
-    //! \param sequence Sequence to which blocks are assigned.
-    //! \return Number of matched tokens from loaded blocks.
-    SizeType32 loadOrAllocateBlocks(std::vector<BlockKey> const& blockKeys, SizeType32 inputLength,
-        SizeType32 numContextBlocks, GenerationRequest& sequence,
-        std::vector<executor::RetentionPriorityAndDuration> const& perBlockRetentions,
-        executor::KvCacheTransferMode mode = executor::KvCacheTransferMode::DRAM, std::string const& directory = "",
-        bool isEnableBlockReuse = false);
-
     //! \brief Phase 1: Walk radix tree and claim matching blocks.
     //! \details Caller must hold mCachedBlocksRootMutex.
     //!          Uses \p tracker to coordinate partial-match ownership across requests in
@@ -1382,10 +1364,6 @@ class BlockManager
 
     void allocatePools(bool useUvm);
 
-    //! \return The number of tokens that were matched/prepopulated from cache (prepopulatedPromptLen)
-    [[nodiscard]] SizeType32 addSequence(GenerationRequest& sequence, SizeType32 inputLength,
-        SizeType32 numContextBlocks, LlmRequest& llmRequest, SizeType32 windowSize, bool isEnableBlockReuse);
-
     //! \brief Batch add sequences forwarding to WindowBlockManager::addSequenceBatch.
     [[nodiscard]] std::vector<WindowBlockManager::BatchSeqStats> addSequenceBatch(
         std::vector<GenerationRequest*> const& sequences, std::vector<SizeType32> const& inputLengths,
@@ -1895,16 +1873,6 @@ class BaseKVCacheManager
     /// LlmRequest::getNumTokens.
     [[nodiscard]] virtual SizeType32 getTokenCount(LlmRequest::RequestIdType requestId) const = 0;
 
-    /// @brief Add new request to the KV cache manager.
-    /// @param inputLength Input length for which KV cache need to be allocated.
-    /// @param beamWidth Beam width for which KV cache need to be allocated.
-    /// @param llmRequest Optional request to use for KV cache lookup.
-    /// @details If llmRequest is supplied and KV cache reuse is enabled, try to recover KV cache blocks for
-    /// inputLength - 1 tokens and populate prepopulatedPromptLen.
-    virtual void addSequence(LlmRequest::RequestIdType requestId, SizeType32 inputLength, SizeType32 beamWidth,
-        OptionalRef<LlmRequest> llmRequest = std::nullopt)
-        = 0;
-
     //! \brief Batch add sequences with two-phase claim-then-onboard strategy.
     //! \details For each attention window, when block reuse is enabled, Phase 1 claims all matching
     //!          blocks across all requests (protecting them from eviction via PartialClaimTracker),
@@ -2276,15 +2244,6 @@ class KVCacheManager : public BaseKVCacheManager
     //! the placeholder block). It should be called before every forward step, after adding new tokens.
     void copyLinearAttentionBlock(LlmRequest const& llmRequest);
 
-    /// @brief Add new request to the KV cache manager.
-    /// @param inputLength Input length for which KV cache need to be allocated.
-    /// @param beamWidth Beam width for which KV cache need to be allocated.
-    /// @param llmRequest Optional request to use for KV cache lookup.
-    /// @details If llmRequest is supplied and KV cache reuse is enabled, try to recover KV cache blocks for
-    /// inputLength - 1 tokens and populate prepopulatedPromptLen.
-    void addSequence(LlmRequest::RequestIdType requestId, SizeType32 inputLength, SizeType32 beamWidth,
-        OptionalRef<LlmRequest> llmRequest = std::nullopt) override;
-
     void addSequenceBatch(
         std::vector<std::tuple<LlmRequest::RequestIdType, SizeType32, SizeType32>> const& requestInfos,
         std::vector<std::reference_wrapper<LlmRequest>> const& llmRequests) override;

cpp/include/tensorrt_llm/batch_manager/kvCacheTransferManager.h

@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2022-2024, NVIDIA CORPORATION.  All rights reserved.
+ * Copyright (c) 2022-2026, NVIDIA CORPORATION.  All rights reserved.
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -63,12 +63,13 @@ class KVCacheTransferManager
     //! \brief Synchronize internal streams with bufferManager stream.
     //! \details The buffer manager uses the same stream as the prefill and decode kernels. This method ensures that the
     //! internal kernels used for offloading and onboarding will wait for prefill and decode kernels before performing
-    //! any block copies. This method must be called before the first call to KVCacheManager::addSequence in every step.
+    //! any block copies. This method must be called before the first call to
+    //! KVCacheManager::addSequenceBatch in every step.
     void syncWithBufferManager();
 
     //! \brief Synchronize bufferManager stream with internal streams. This method ensures that prefill and decode
     //! kernels for next step will wait for offloading and onboarding work that has already been scheduled. This method
-    //! must be called after last call to KVCacheManager::addSequence in every step.
+    //! must be called after the last call to KVCacheManager::addSequenceBatch in every step.
     void syncTransfers();
 
     //! \brief Get transfer stats accumulated since last call, and reset the counters.

cpp/include/tensorrt_llm/batch_manager/llmRequest.h

@@ -2002,7 +2002,7 @@ class GenericLlmRequest
     // getRemainingBlocksToCompletion) so that the micro batch scheduler
     // can account for cached tokens when computing the token budget.
     // Marked mutable because it is a cache/estimate set during const
-    // capacity-scheduler queries. Reset to 0 after addSequence sets
+    // capacity-scheduler queries. Reset to 0 after addSequenceBatch sets
     // the authoritative mPrepopulatedPromptLen and advances context position.
     mutable SizeType32 mEstimatedReusableTokens{0};
 

cpp/tensorrt_llm/batch_manager/allocateKvCache.cpp

@@ -1,5 +1,5 @@
 /*
- * SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+ * SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
  * SPDX-License-Identifier: Apache-2.0
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
@@ -19,6 +19,8 @@
 #include "tensorrt_llm/common/logger.h"
 #include "tensorrt_llm/common/nvtxUtils.h"
 
+#include <functional>
+
 void tensorrt_llm::batch_manager::AllocateKvCache::operator()(BaseKVCacheManager& kvCacheManager,
     RequestVector& contextRequests, RequestVector const& generationRequests, runtime::ModelConfig const& modelConfig,
     OptionalRef<BaseKVCacheManager> crossKvCacheManager) const
@@ -38,7 +40,7 @@ void tensorrt_llm::batch_manager::AllocateKvCache::operator()(BaseKVCacheManager
             auto draftLength = llmReq->getNumDraftTokens();
 
             // Allocate/Reuse KV cache
-            kvCacheManager.addSequence(requestId, promptLen, reqBeamWidth, llmReq);
+            kvCacheManager.addSequenceBatch({{{requestId, promptLen, reqBeamWidth}}}, {std::ref(*llmReq)});
 
             // EagleNet will increment kv cache up to maxPathLen to account for accepted tokens.
             // Then up to maxDecodingDraftTokens will be used to generate next draft tokens.
@@ -59,7 +61,8 @@ void tensorrt_llm::batch_manager::AllocateKvCache::operator()(BaseKVCacheManager
 
             if (crossKvCacheManager)
             {
-                crossKvCacheManager->addSequence(requestId, llmReq->getEncoderOutputLen(), reqBeamWidth, llmReq);
+                crossKvCacheManager->addSequenceBatch(
+                    {{{requestId, llmReq->getEncoderOutputLen(), reqBeamWidth}}}, {std::ref(*llmReq)});
             }
         }
     }