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cs.DC2026
SPLASH: Switching Parallel Layouts of Attention with Seamless Handoff for LLM Serving
Chuan Liu, Shuoming Zhang, Zhicheng Li +6
No single way of parallelizing attention serves large language models well under all loads. Low concurrency favors tensor parallelism, many independent requests favor data-parallel…
cs.DC2026
Ave: Guiding Agentic GPU Optimization Using Data-Flow Invariants
Haohui Mai, Xiaoyan Guo, Xiangyun Ding +7
LLM coding agents can generate correct GPU kernels, but their performance still trails expert libraries. Reaching peak throughput requires coordinating low-level optimizations such…