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.
Mooncake: A kvcache-centric disaggregated architecture for llm serving
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SPECTRE achieves up to 2.28x speedup for large-model LLM serving by running speculative draft generation and target verification in parallel using idle tail-model services.
SplitZip introduces a fast lossless KV cache compressor for disaggregated LLM inference that achieves 613 GB/s compression throughput on BF16 tensors and up to 1.32x end-to-end speedup.
NetKV is a network-aware O(|D|) greedy scheduler for decode instance selection that reduces mean TTFT by up to 21.2% versus round-robin and 17.6% versus cache+load baselines in 64-GPU fat-tree simulations.
citing papers explorer
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SPECTRE: Hybrid Ordinary-Parallel Speculative Serving for Resource-Efficient LLM Inference
SPECTRE achieves up to 2.28x speedup for large-model LLM serving by running speculative draft generation and target verification in parallel using idle tail-model services.
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SplitZip: Ultra Fast Lossless KV Compression for Disaggregated LLM Serving
SplitZip introduces a fast lossless KV cache compressor for disaggregated LLM inference that achieves 613 GB/s compression throughput on BF16 tensors and up to 1.32x end-to-end speedup.