DAK enables direct GPU access to remote memory for LLM inference via TMA repurposing and a greedy offloading algorithm, achieving up to 3x gains over prefetching baselines on NVLink-C2C and 1.8x on PCIe.
Taming {Throughput-Latency} tradeoff in {LLM} inference with {Sarathi-Serve}
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
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CompactAttention accelerates chunked-prefill attention via Block-Union KV Selection, delivering up to 2.72x speedup at 128K context on LLaMA-3.1-8B while matching dense accuracy on RULER.
citing papers explorer
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DAK: Direct-Access-Enabled GPU Memory Offloading with Optimal Efficiency for LLM Inference
DAK enables direct GPU access to remote memory for LLM inference via TMA repurposing and a greedy offloading algorithm, achieving up to 3x gains over prefetching baselines on NVLink-C2C and 1.8x on PCIe.
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CompactAttention: Accelerating Chunked Prefill with Block-Union KV Selection
CompactAttention accelerates chunked-prefill attention via Block-Union KV Selection, delivering up to 2.72x speedup at 128K context on LLaMA-3.1-8B while matching dense accuracy on RULER.