Chiplet design space stops being a black box: LLM sets direction, Bayesian optimization does the numbers
Feeding an LLM's parameter-adjustment directions to Bayesian optimization as a soft prior raises hypervolume on a 3D CPU-GPU chiplet design space from 0.8210 to 0.8356, and to 0.8051 on a 2.5D space without retraining.