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.
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).