implementation detail · filed under inference & serving
Sparse hash-aligned KDA recurrent-state checkpoints
Saves recurrent-state checkpoints only at selected MLA hash endpoints that cache lookups can reference.
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- model
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- lab adopt it
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How sources treat it
One count per evidence span, weakest treatment to strongest.
core 1
Documented in
Evidence
1 span quoted from the sources, strongest treatment first.
checkpoints of the recurrent state are saved only at (a sparse subset of) MLA’s hash endpoints—the only positions a lookup can ever reference.
coreinference servingin Kimi K3Moonshot AI
Filed alongside
Other methods under inference & serving :: KV cache management.
Chunked prefillPrefix cachingPrompt cachingSWA Bounded ReplayLanguage-model-only serving modePeriodic cache checkpointingCompressed KV cachingKDA-aware prefix-cache managementRadixCacheZero SWA caching8-bit Mamba cache quantizationAsynchronous cache offloading and restorationAutomatic cacheBlock-based KV cacheCross-layer KV-cache reuseCustomized heterogeneous KV-cache layoutDisable prefix caching for benchmarkingDynamic allocation of fixed-size state-cache poolsEncoder SWA bounded replayExact SWA KV reconstruction via full multi-layer replayFine-grained prefix hashingHierarchical KV cachingInference-side KV-cache reset on weight synchronizationKDA with prefill cache