Applicability of neuromorphic hardware in disease spread simulations : A comparison of a SpiNNaker board and a GPU

Abstract: This research paper investigates whether neuromorphic hardware can outperform the traditional GPU in simulating disease spread. As the era of Moore’s Law draws to a close, researchers are seeking alternative solutions to enhance computational power. Larger disease spread simulations, crucial for studying and assessing preventive measures, are becoming constrained as supercomputers struggle to process them quickly enough. To meet the demand for improved computational performance in disease spreading simulations, neuromorphic hardware, designed to mimic the structure and functionality of the brain, offers an intriguing alternative to current technology. By comparing the performance of a disease spread simulation implemented on a NVIDIA GPU and a SpiNNaker machine, this study demonstrates that the GPU outperforms the tested neuromorphic hardware. However, when comparing the runtime phase during which the simulation is executed, the SpiNNaker showed a constant time complexity whereas the GPU showed a linear time complexity. The study highlights the potential of neuromorphic hardware for more efficient disease spread simulations in the future, given further advancements in the technology.