TY - JOUR
T1 - Dense agent-based HPC simulation of cell physics and signaling with real-time user interactions
AU - Merchant, Naman
AU - Sampson, Adam T.
AU - Boiko, Andrei
AU - Falconer, Ruth E.
PY - 2023/5/12
Y1 - 2023/5/12
N2 - Introduction: Distributed simulations of complex systems to date have focused on scalability and correctness rather than interactive visualization. Interactive visual simulations have particular advantages for exploring emergent behaviors of complex systems. Interpretation of simulations of complex systems such as cancer cell tumors is a challenge and can be greatly assisted by using “built-in” real-time user interaction and subsequent visualization. Methods: We explore this approach using a multi-scale model which couples a cell physics model with a cell signaling model. This paper presents a novel communication protocol for real-time user interaction and visualization with a large-scale distributed simulation with minimal impact on performance. Specifically, we explore how optimistic synchronization can be used to enable real-time user interaction and visualization 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 utilized. The key features of the High-Performance Computing (HPC) simulation that were evaluated are scalability, deterministic verification, speed of real-time user interactions, and deadlock avoidance. Results: We use two commodity HPC systems, ARCHER (118,080 CPU cores) and ARCHER2 (750,080 CPU cores), where we simulate up to 256 million agents (one million cells) using up to 21,953 computational cores and record a response time overhead of ≃350 ms from the issued user events. Discussion: The approach is viable and can be used to underpin transformative technologies offering immersive simulations such as Digital Twins. The framework explained in this paper is not limited to the models used and can be adapted to systems biology models that use similar standards (physics models using agent-based interactions, and signaling pathways using SBML) and other interactive distributed simulations.
AB - Introduction: Distributed simulations of complex systems to date have focused on scalability and correctness rather than interactive visualization. Interactive visual simulations have particular advantages for exploring emergent behaviors of complex systems. Interpretation of simulations of complex systems such as cancer cell tumors is a challenge and can be greatly assisted by using “built-in” real-time user interaction and subsequent visualization. Methods: We explore this approach using a multi-scale model which couples a cell physics model with a cell signaling model. This paper presents a novel communication protocol for real-time user interaction and visualization with a large-scale distributed simulation with minimal impact on performance. Specifically, we explore how optimistic synchronization can be used to enable real-time user interaction and visualization 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 utilized. The key features of the High-Performance Computing (HPC) simulation that were evaluated are scalability, deterministic verification, speed of real-time user interactions, and deadlock avoidance. Results: We use two commodity HPC systems, ARCHER (118,080 CPU cores) and ARCHER2 (750,080 CPU cores), where we simulate up to 256 million agents (one million cells) using up to 21,953 computational cores and record a response time overhead of ≃350 ms from the issued user events. Discussion: The approach is viable and can be used to underpin transformative technologies offering immersive simulations such as Digital Twins. The framework explained in this paper is not limited to the models used and can be adapted to systems biology models that use similar standards (physics models using agent-based interactions, and signaling pathways using SBML) and other interactive distributed simulations.
KW - complex system simulations
KW - parallel agent-based simulation
KW - cell physics
KW - drug discovery
KW - rollback and recover
KW - ARCHER
KW - ARCHER2
KW - real-time interactions
UR - http://www.scopus.com/inward/record.url?scp=85160083370&partnerID=8YFLogxK
U2 - 10.3389/fcomp.2023.1085867
DO - 10.3389/fcomp.2023.1085867
M3 - Article
SN - 2624-9898
VL - 5
JO - Frontiers in Computer Science
JF - Frontiers in Computer Science
M1 - 1085867
ER -
