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cs.AR2026
ECO: Energy-Oriented Configuration Optimization for Attention FFN Disaggregated LLM Serving
Zou Qingyun, Bin Gao, Zhuobin Huang +3
Energy-efficient LLM serving requires minimizing serving GPU energy while meeting latency and throughput service-level objectives (SLOs). Attention--FFN disaggregation (AFD) enable…
cs.AR2026
SPLASH: Co-Designing Sparse Attention with High-Bandwidth Flash for Efficient Long-Context Inference
Aditya Anirudh Jonnalagadda, Agasthi Haputhanthri, Pranav Dangi +5
The key-value (KV) cache has become the dominant consumer of memory in large language model (LLM) serving systems as context lengths, concurrency, and request lifetimes grow. High-…
cs.AR2026
Accelerating Multi-Scale Deformable Attention Using Near-Memory-Processing Architecture
Huize Li, Qinggang Wang, Bing Gao +3
Multi Scale Deformable Attention (MSDAttn) has become a fundamental component in various vision tasks due to its effective multi scale grid sampling (MSGS). However, its reliance o…