LLMulator uses an LLM with digit-wise numeric output, DPO-based dynamic calibration, and synthetic data augmentation to predict dataflow accelerator performance, reporting 12.2% mean absolute percentage error.
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LLMulator: Generalizable Cost Modeling for Dataflow Accelerators with Input-Adaptive Control Flow
LLMulator uses an LLM with digit-wise numeric output, DPO-based dynamic calibration, and synthetic data augmentation to predict dataflow accelerator performance, reporting 12.2% mean absolute percentage error.