AI RESEARCH
Dooly: Configuration-Agnostic, Redundancy-Aware Profiling for LLM Inference Simulation
arXiv CS.AI
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ArXi:2605.07985v1 Announce Type: cross Selecting the optimal LLM inference configuration requires evaluation across hardware, serving engines, attention backends, and model architectures, since no single choice performs best across all workloads. Profile-based simulators are the standard tool, yet they hardcode their operation set to a specific configuration and re-profile every operation from scratch, making exploration prohibitively expensive.