PyDGGA: Distributed GGA for Automatic Configuration

We present PYDGGA, a Python tool that implements a distributed version of the automatic algorithm configurator GGA, which is a specialized genetic algorithm to find high quality parameters for solvers and algorithms. PYDGGA implements GGA using an event-driven architecture and runs a simulation of future generations of the genetic algorithm to maximize the usage of the available computing resources. Overall, PYDGGA offers a friendly interface to deploy elastic distributed AC scenarios on shared high-performance computing clusters.