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Back in the day, "stochastic superoptimization" would be a reasonable description for an application of genetic programming. Guess I will have to read the paper to understand what's new.


Yes, genetic programming arguably goes back to Turing which is way back in the day, but the term superoptimizer goes back to Henry Masselin's 1987 paper, Superoptimizer - a look at the smallest program.

https://web.stanford.edu/class/cs343/resources/cs343-annot-s...


Thanks for the pointer. Yeah, re: GP I was more referring to the work that came with Holland and after.

Re: "smallest program" I will always think of Tom Ray's Tierra. Went to a demo of his in 1991, mind-blowing.

https://www.cc.gatech.edu/~turk/bio_sim/articles/tierra_thom...


I think superoptimisation refers to it doing a type of program optimisation beyond what an optimising compiler would do.

GP is certainly on-topic here! People are using GP to do this kind of thing too. But I think this system is not using GP.


Superoptimization is a methodology for building an optimizer. When you run a superoptimizer it’s “just” doing peephole optimization. Although, it’s similar to comparing bogo sort (regular opt) to sorting networks (super opt).


And "stochastic superoptimization" sounds so much cooler than their original term; "super-duper random improvement."




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