Fireflies: New software for interactively exploring dynamical systems using GPU computing

TL;DR

Fireflies is GPU-accelerated software that enables real-time, interactive visualization of complex dynamical systems by simulating millions of trajectories, aiding understanding and teaching of non-linear models.

Contribution

The paper introduces Fireflies, a novel GPU-based software for interactive visualization of dynamical systems, capable of handling millions of trajectories in real-time.

Findings

Real-time visualization of complex systems achieved

Demonstrated with neuronal, Lorenz, and high-dimensional models

Interactive parameter changes reveal bifurcations and attractors

Abstract

In non-linear systems, where explicit analytic solutions usually can't be found, visualisation is a powerful approach which can give insights into the dynamical behaviour of models; it is also crucial for teaching this area of mathematics. In this paper we present new software, Fireflies, which exploits the power of graphical processing unit (GPU) computing to produce spectacular interactive visualisations of arbitrary systems of ordinary differential equations. In contrast to typical phase portraits, Fireflies draws the current position of trajectories (projected onto 2D or 3D space) as single points of light, which move as the system is simulated. Due to the massively parallel nature of GPU hardware, Fireflies is able to simulate millions of trajectories in parallel (even on standard desktop computer hardware), producing "swarms" of particles that move around the screen in real-time according to the equations of the system. Particles that move forwards in time reveal stable attractors (e.g. fixed points and limit cycles), while the option of integrating another group of trajectories backwards in time can reveal unstable objects (repellers). Fireflies allows the user to change the parameters of the system as it is running, in order to see the effect that they have on the dynamics and to observe bifurcations. We demonstrate the capabilities of the software with three examples: a two-dimensional "mean field" model of neuronal activity, the classical Lorenz system, and a 15-dimensional model of three interacting biologically realistic neurons.