In Situ Visualization for 3D Agent-Based Vocal Fold Inflammation and Repair Simulation

Area of Science:

• Computational Biology
• Systems Biology
• Bioinformatics

Background:

• Accurate modeling of biological systems requires efficient visualization of large datasets.
• In situ visualization techniques are crucial for handling high-fidelity simulation data and enabling computational steering.
• Existing methods often face I/O bottlenecks and high resource demands.

Purpose of the Study:

• To develop a high-performance scheme for coupling in situ visualization with biological simulations.
• To enable real-time analysis of vocal fold inflammation and repair models with minimal computational cost.
• To create a system biology simulation suite for remote simulation and visualization.

Main Methods:

• Implemented an adaptive sampling scheme to optimize visualization rendering speed and precision.
• Utilized VirtualGL for efficient in situ visualization.
• Overlapped visualization and simulation processes for optimal resource utilization.

Main Results:

• Achieved a novel high-performance in situ visualization scheme with negligible extra cost.
• Developed a system capable of simulating 17 million cells and 1.2 billion data points.
• Enabled real-time remote visualization with aggregated statistics delivery.

Conclusions:

• The developed in situ visualization scheme significantly enhances the efficiency of biological system modeling.
• This approach facilitates detailed analysis of complex biological processes like vocal fold repair.
• The system offers powerful capabilities for remote simulation and real-time data interpretation.