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Efficient Memory Management for Large Language Model Serving with PagedAttention

Paper summary

PagedAttention stores attention caches in noncontiguous blocks and permits sharing where appropriate. The vLLM serving implementation reduces fragmentation and redundant cache storage, improving evaluated throughput under comparable latency.

Relevance to the project

An allocation and capacity-management reference for optional LLM serving. Blocked storage may also inspire bounded history pools, subject to different simulation access patterns.

Language modelsAttentionEfficient inferenceLong-context processing

Cache paging does not solve deterministic graph-update ordering.

Source record

Reference ID
pagedattention
Archived version
2309.06180v1
Summary provenance
reference-library/papers/pagedattention/metadata.json · summary
Review status
initial orientation summary; not a critical full-paper review
Reading scope
Selected abstract/opening and available closing discussion/conclusion passages in the preserved text extract; broader project notes provide context. No reproduction of experiments, exhaustive methods review, or equation/figure audit.