[lmcafee-nvidia]

What does this PR do ?

Add Mamba state prefix caching for hybrid Transformer-Mamba models, enabling KV cache prefix sharing to also share corresponding Mamba conv/SSM states.

Key Features

• Mamba state caching: When KV cache blocks are reused due to shared prefixes, the corresponding Mamba states can now also be cached and restored, avoiding redundant recomputation
• Memory-budgeted cache: New --inference-dynamic-batching-prefix-caching-mamba-gb argument controls the memory budget for cached Mamba states
• LRU eviction: Mamba cache uses LRU eviction based on KV block timestamps when the cache is full
• Automatic invalidation: When KV blocks are evicted, their associated Mamba states are automatically invalidated

Changes

Core Implementation (megatron/core/inference/contexts/dynamic_context.py, megatron/core/inference/engines/dynamic_engine.py):

• Fixed-size tensor pool for cached Mamba conv/SSM states
• Block-to-slot mapping for associating KV blocks with Mamba cache slots
• Store Mamba state at block boundaries after prefill completes
• Restore cached Mamba state when prefix matches during request scheduling

Block Allocator (megatron/core/inference/contexts/dynamic_block_allocator.py):

• Invalidate Mamba state when KV blocks are evicted

Arguments (megatron/training/arguments.py):

• Add --inference-dynamic-batching-prefix-caching-mamba-gb parameter
• Auto-enable chunked prefill when Mamba prefix caching is used

Test plan

• Unit tests for cache allocation/deallocation
• Unit tests for LRU eviction (20 tests in tests/unit_tests/inference/contexts/test_mamba_prefix_caching.py)
• Tests for memory budget edge cases
• Tests for state store/restore integration
• End-to-end inference test with hybrid model

⚠️ For major changes (either in lines of code or in its impact), please make sure to first share a design doc with the team. If you're unsure what's the best way to do so, contact the @mcore-oncall.

Contribution process

flowchart LR
    A[Pre-checks] --> B[PR Tests]
    subgraph Code Review/Approval
        C1[Expert Review] --> C2[Final Review]
    end
    B --> C1
    C2 --> D[Merge]

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Pre-checks

• I want this PR in a versioned release and have added the appropriate Milestone (e.g., Core 0.8)
• I have added relevant unit tests
• I have added relevant functional tests
• I have added proper typing to my code Typing guidelines
• I have added relevant documentation
• I have run the autoformatter.sh on my PR

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[lmcafee-nvidia]

/ok to test ee7dfa7

[svcnvidia-nemo-ci]

🔄 Merge queue validation started!

You can track the progress here: https://github.com/NVIDIA/Megatron-LM/actions/runs/23231656658

[svcnvidia-nemo-ci]

🔄 Merge queue validation started!

You can track the progress here: https://github.com/NVIDIA/Megatron-LM/actions/runs/23233038271

[svcnvidia-nemo-ci]

🔄 Merge queue validation started!

You can track the progress here: https://github.com/NVIDIA/Megatron-LM/actions/runs/23234613368