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The Price of Precision: A Calibrated Cost Model for Mixed-Precision LLM Serving

Athmaram, Mukund et al.
arXiv (All) · Papers
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machine-learning
Choosing a mixed-precision configuration for large language model (LLM) serving trades speed against accuracy. Allocators that use average bit-width or a memory budget as a speed proxy can miss changes in the resource that limits execution. We argue that served speed can be limited by compute, weigh
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