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Here is the relevant bit from their whitepaper ( https://storage.googleapis.com/deepmind-media/DeepMind.com/B... ): > AlphaEvolve was able to find a simple code rewrite (within an …

Existing mixed-placement algorithms depend on hyperparameters, heuristics, and initial states / randomness. If afforded more compute resources, they can explore a much wider space …

Cadence in particular has been quite receptive to allowing academics and researchers to benchmark new algorithms against their tools. They have also been quite permissive with lett…

So I'm not sure what Google is referring to here. As you can see in the ISPD paper ( https://vlsicad.ucsd.edu/Publications/Conferences/396/c396.p... ) on page 5, they openly compar…

> One key argument in the rebuttal against the ISPD article is that the resources used in their comparison were significantly smaller. To me, this point alone seems sufficient to q…

You are correct. For commercial use, the GPUs used for training and fine-tuning aren't a problem financially. However, if we wanted to rigorously benchmark AlphaChip against simula…

I have published an addendum to an article I wrote about AlphaChip ( https://vighneshiyer.com/misc/ml-for-placement/ ) at the very bottom that addresses this rebuttal from Google a…

This work from Google (original Nature paper: https://www.nature.com/articles/s41586-021-03544-w ) has been credibly criticized by several researchers in the EDA CAD discipline. Th…