  Large-scale simulation with realistic nonlinear dynamic models is crucial for
algorithms development for swarm robotics. However, existing platforms are
mainly developed based on Object-Oriented Programming (OOP) and either use
simple kinematic models to pursue a large number of simulating nodes or
implement realistic dynamic models with limited simulating nodes. In this
paper, we develop a simulator based on Data-Oriented Programming (DOP) that
utilizes GPU parallel computing to achieve large-scale swarm robotic
simulations. Specifically, we use a multi-process approach to simulate
heterogeneous agents and leverage PyTorch with GPU to simulate homogeneous
agents with a large number. We test our approach using a nonlinear quadrotor
model and demonstrate that this DOP approach can maintain almost the same
computational speed when quadrotors are less than 5,000. We also provide two
examples to present the functionality of the platform.
