ai.hackcv
论文精选 83arXiv

vToken: Token-Level Virtualization for Reclaimable KV Caches· vToken:面向未来的 KV 缓存虚拟化技术

Large language model serving faces a critical memory bottleneck: the KV cache grows with sequence length and batch size. PagedAttention uses fixed-size memory blocks to reduce allocator-level fragmentation, but recent KV eviction algorithms operate at a token granularity finer than block-level management. This mismatch causes intra-block fragmentation, leaving a large fraction of allocated KV memory unreclaimable. We present vToken, a lightweight token-level virtualization layer that decouples logical token liveness from physical block placement. vToken maintains a stable logical token view through token-table indirection and realizes physical reclamation by repacking live tokens asynchronously. The design preserves PagedAttention kernels and CUDA Graph compatibility. We implement vToken i

领域:cs.AI作者:Yuanhang Gao、Xiangrui Yang、Yuanfeng Chen
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