CHESS: Context-aware Hierarchical Efficient Semantic Selection for Long-Context LLM Inference

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• CHESS achieves low-latency stable inference with up to 4.56x higher throughput compared to baselines.result 95%
• CHESS surpasses Full-KV quality using only 1% of the KV cache.result 95%
• CHESS is an algorithm-system co-design KV-cache management system.method 90%
• CHESS introduces a context-aware, hierarchical selection policy for dynamic context reconstruction.method 90%
• CHESS's coarse granularity selection eliminates expensive data movement, realizing practical acceleration from theoretical sparsity.technical 90%
• CHESS could replace current LLM deployment strategies hampered by memory bandwidth limitations.market 80%
• The implementation of CHESS may require adaptation to diverse infrastructure environments.limitation 70%
• There may be undiscovered edge cases where CHESS's context-aware reconstruction might not perform optimally.limitation 70%

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