The Nature paper describes the importance of pre-training repeatedly. The ability to learn from experience is the whole point of the method. Pre-training is just training and saving the weights -- this is ML 101.
I'm glad you agree that HPWL is a proxy metric. Optimizing HPWL is a fun applied math puzzle, but it's not chip design.
I am unaware of a single instance of someone using SA to generate real-world, usable macro layouts that were actually taped out, much less for modern chip design, in part due to SA's struggles to manage congestion, resulting in unusable layouts. SA converges quickly to a bad solution, but this is of little practical value.
I'm glad you agree that HPWL is a proxy metric. Optimizing HPWL is a fun applied math puzzle, but it's not chip design.
I am unaware of a single instance of someone using SA to generate real-world, usable macro layouts that were actually taped out, much less for modern chip design, in part due to SA's struggles to manage congestion, resulting in unusable layouts. SA converges quickly to a bad solution, but this is of little practical value.