Scalable agent-based HPC simulation of cell physics and signalling with real-time user interactions

Abstract

Distributed simulations of complex systems to date have focused on scalability and correctness rather than interactive visualisation. Interactive visual simulations have particular advantages for exploring emergent behaviours of complex systems. Interpretation of simulations of complex systems such as cancer cell tumours is a challenge and can be greatly assisted by using built-in real-time user interaction and subsequent visualisation. We explore this approach using a multi-scale model which couples a cancer cell physics model with a cell signalling model. This project describes how optimistic synchronisation can be used as a checkpoint strategy to enable real-time user interaction and visualisation in a densely packed parallel agent-based simulation, whilst maintaining scalability and determinism. We also describe the software framework created and the distribution strategy for the models utilised. The features of the HPC simulation evaluated are scalability, deterministic verification, real-time user interactions, and deadlock avoidance. We use two commodity HPC systems, ARCHER and ARCHER2 where we simulate up to 256 million agents (one million cells) and record a good response time overhead of ≃350ms from the issued user events. The approach is viable and can be used to underpin transformative technologies offering immersive simulations such as Digital Twins. The framework explained in this thesis is not limited to the models used, and can easily be adapted to systems biology models that use similar standards (physics models using agent-based interactions, and signalling pathways using SBML).

Date of Award	27 Oct 2023
Original language	English
Awarding Institution	Abertay University
Sponsors	Northwood Charitable Trust
Supervisor	Ruth Falconer (Supervisor), Adam T. Sampson (Supervisor) & Andrei Boiko (Supervisor)