Native Dual Pools or Shared Paging? Memory Organization for Concurrent Hybrid LLM Serving
Abstract: Hybrid attention-SSM serving combines growing attention KV with fixed-size recurrent and convolution state whose allocation units, reuse boundaries, and lifetimes differ. We implement four memory organizations in a modified vLLM runtime: a coarse shared-page baseline (S0), checkpoint-internal recurrent paging (S1), paging with convolution-slot packing (S2), and native dual pools (D0). Nine evaluation questions cover storage costs and serving behavior. The cumulative S0-S1-S2 refinement improves completed-output throughput and tail completion time at the main operating point. D0-S2 performance varies with memory budget, offered load, and admission headroom. Shared-prefix workloads yield larger stepwise gains; gains also persist in a no-sharing control with equal recorded input-work totals. State traces identify recurrent-checkpoint availability as the limit on joint reuse in the tested S2 runs. Extending producer-side checkpoint lifetime increases reusable depth at a fixed page budget. A fresh-seed SHARE/ISOLATE comparison estimates a positive retention interaction, with a primary confidence interval that includes zero. Retained-state continuation correctness remains unresolved. These findings motivate evaluating physical state representation together with request admission and checkpoint lifetime when designing memory management for concurrent hybrid-model serving.