April 30, 2021

About the speakers

Ms. Kassandra Guerra, Mr. Jose Garces and Ms. Thalia Juarez are undergraduate students in Computer Science.

High-Performance Computations for Random Network Models of Parental Vaccine Acceptance and Disease Spread

An agent-based random network model is considered with four overlapping network models. The nodes represent households with parents and children within them. One network represents the children's physical connections through which disease spreads. The other network represents the parents' social network through which information is exchanged about the disease and the vaccine. The stochastic network model is implemented using the CuPy open-source Python library with accelerated matrix and vector operations on multiple NVIDIA GPUs. The key result from this work is a high-performance program that generates multiple overlapping networks, producing robust data for future mathematics research.