On a real multi-node H100 cluster the authors show that for MLA, routing the ~1 KB compressed query row is cheaper than moving cache chunks and supply a topology-aware cost model accurate to ~7% on IBGDA fabrics.
MEPIC: Memory efficient position independent caching for LLM serving
4 Pith papers cite this work. Polarity classification is still indexing.
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Hypic enables position-independent KV caching for hybrid-attention models via segment-cumulative operators and boundary seam recomputation, delivering 2.45x average TTFT reduction and up to 2.0x throughput gain.
MiniPIC enables multiple position-independent caching methods inside vLLM via unrotated KV storage, per-request RoPE application, and three primitives, delivering 49% prefill throughput gains and up to 100x lower cached-span TTFT on 2WikiMultihopQA.
Irminsul recovers up to 83% of prompt tokens above exact-prefix matching and delivers 63% prefill energy savings per cache hit on MLA-MoE models by content-hashing CDC chunks and applying closed-form kr correction.
citing papers explorer
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Move the Query, Not the Cache: Characterizing Cross-Instance Latent Attention Redistribution Across GPU Fabrics
On a real multi-node H100 cluster the authors show that for MLA, routing the ~1 KB compressed query row is cheaper than moving cache chunks and supply a topology-aware cost model accurate to ~7% on IBGDA fabrics.
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HYPIC: Accelerating Hybrid-Attention LLM Serving with Position-Independent Caching
Hypic enables position-independent KV caching for hybrid-attention models via segment-cumulative operators and boundary seam recomputation, delivering 2.45x average TTFT reduction and up to 2.0x throughput gain.
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Irminsul: MLA-Native Position-Independent Caching for Agentic LLM Serving
Irminsul recovers up to 83% of prompt tokens above exact-prefix matching and delivers 63% prefill energy savings per cache hit on MLA-MoE models by content-hashing CDC chunks and applying closed-form kr correction.