Scalable Symbolic Regression by Continuous Evolution with Very Small Populations

The future of computing is one of massive parallelism. To exploit this and generatemaximumperformance itwill be inevitable thatmore co-design between hardware and software takes place. Many software algorithms need rethinking to expose all the possible concurrency, increase locality and have built-in fault tolerance. Evolutionary algorithms are naturally parallel and should as such have an edge in exploiting these hardware features.