Abstract
A fast and insightful visualization is essential in modeling biological system behaviors and understanding underlying inter-cellular mechanisms. High fidelity models produce billions of data points per time step, making in situ visualization techniques extremely desirable as they mitigate I/O bottlenecks and provide computational steering capability. In this work, we present a novel high-performance scheme to couple in situ visualization with the simulation of the vocal fold inflammation and repair using little to no extra cost in execution time or computing resources. The visualization component is first optimized with an adaptive sampling scheme to accelerate the rendering process while maintaining the precision of the displayed visual results. Our software employs VirtualGL to perform visualization in situ. The scheme overlaps visualization and simulation, resulting in the optimal utilization of computing resources. This results in an in situ system biology simulation suite capable of remote simulation of 17 million biological cells and 1.2 billion chemical data points, remote visualization of the results, and delivery of visualized frames with aggregated statistics to remote clients in real-time.
Highlights
Agent-based modeling (ABM) is a powerful and widely used approach to simulate a system consisting of interacting components or agents
We extend our previous work on a fast GPU implementation of vocal fold (VF) ABM simulation to incorporate in situ visualization at no extra cost to the overall simulation
We presented novel techniques to achieve in situ 3D ABM visualization at almost no cost to the overall simulation
Summary
Agent-based modeling (ABM) is a powerful and widely used approach to simulate a system consisting of interacting components or agents. In ABM, agents are used to represent a wide spectrum of entities such as animals in ecosystems [13, 18, 24, 25], consumers and markets in economic models [3, 10, 36,37,38,39], and cells and proteins in biological systems [9, 11, 12, 17, 20,21,22,23, 31, 32, 34, 41] These entities interact among themselves and with their environment (ABM world ) in discrete time steps following a set of stochastic and/or deterministic rules.
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