Error-Safe, Portable, and Efficient Evolutionary Algorithms Implementation with High Scalability

Abstract

We present an efficient massively parallel implementation of genetic algorithms for chemical and materials science problems, solely based on Java virtual machine (JVM) technologies and standard networking protocols. The lack of complicated dependencies allows for a highly portable solution exploiting strongly heterogeneous components within a single computational context. At runtime, our implementation is almost completely immune to hardware failure, and additional computational resources can be added or subtracted dynamically, if needed. With extensive testing, we show that despite all these benefits, parallel scalability is excellent.