Real-Time Agent-Based Modeling Simulation with in-Situ Visualization of Complex Biological Systems: A Case Study on Vocal Fold Inflammation and Healing

Seekhao, Nuttiiya; Shung, C.B.; JáJá, Joseph F.; Mongeau, Luc; Li‐Jessen, Nicole Y. K.

doi:10.1109/ipdpsw.2016.20

Cited by 8 publications

(12 citation statements)

References 29 publications

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“…Often, this tendency results in idle CPU cores, since their only job is to transfer data and launch GPU tasks, while the GPUs perform all the computing work. We proposed a host-device computation overlap technique in our earlier work [32], which results in state-of-the-art performance for multi-scale 2D bio-simulation ABMs. Since the 3D model is substantially more computationally demanding, we significantly extend the methods described there to achieve extremely high speed 3D simulation with in situ visualization.…”

Section: A Novel Approachmentioning

confidence: 99%

“…Model operations are divided into sub-tasks and categorized as coarse or fine [32]. Since coarse-grain tasks (inflammatory cell and ECM function) are complex but less data-intensive, they are deemed CPU-suitable, where simple data-intensive fine-grain (chemical diffusion) and rendering tasks run most effectively on GPUs.…”

Section: A Novel Approachmentioning

confidence: 99%

“…As opposed to the analytical, equation-based approaches, the agent-based approach offers the ability to add complex behaviors to individual components or agents , making modeling of composite networks uncomplicated [8, 15]. In ABM, agent s 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, 36–39], and cells and proteins in biological systems [9, 11, 12, 17, 20–23, 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.…”

Section: Introductionmentioning

confidence: 99%

“…Section 2 discusses approaches taken to enhance visualization resolution, while keeping visualization performance optimized to enable a complete masking of the visualization cost, using our CPU-GPU task scheduling scheme [32, 33]. Performance and resolution enhancement evaluation is discussed in section 3.…”

Section: Introductionmentioning

confidence: 99%

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

Seekhao

JáJá

Mongeau

et al. 2017

JSFI

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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.

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Section: A Novel Approachmentioning

confidence: 99%

Section: A Novel Approachmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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

Seekhao

JáJá

Mongeau

et al. 2017

JSFI

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“…The concept of coarse-graining in ABM refers to the simulation of super-agents whose rules represent aggregated behaviors of smaller units (Chang and Harrington, 2006 ; Maus et al, 2011 ; Sneddon et al, 2011 ). Our earlier 2D framework uses a mechanism that captures the behavior of multiple iterations of the finer-scale processes, i.e., chemical diffusion, over a coarse time window using convolution (Seekhao et al, 2016 ). This intensive computation is then offloaded to a single GPU while the CPU cores focus on coarse-grain cellular processes.…”

Section: Introductionmentioning

confidence: 99%

High-Performance Agent-Based Modeling Applied to Vocal Fold Inflammation and Repair

et al. 2018

Self Cite

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Fast and accurate computational biology models offer the prospect of accelerating the development of personalized medicine. A tool capable of estimating treatment success can help prevent unnecessary and costly treatments and potential harmful side effects. A novel high-performance Agent-Based Model (ABM) was adopted to simulate and visualize multi-scale complex biological processes arising in vocal fold inflammation and repair. The computational scheme was designed to organize the 3D ABM sub-tasks to fully utilize the resources available on current heterogeneous platforms consisting of multi-core CPUs and many-core GPUs. Subtasks are further parallelized and convolution-based diffusion is used to enhance the performance of the ABM simulation. The scheme was implemented using a client-server protocol allowing the results of each iteration to be analyzed and visualized on the server (i.e., in-situ) while the simulation is running on the same server. The resulting simulation and visualization software enables users to interact with and steer the course of the simulation in real-time as needed. This high-resolution 3D ABM framework was used for a case study of surgical vocal fold injury and repair. The new framework is capable of completing the simulation, visualization and remote result delivery in under 7 s per iteration, where each iteration of the simulation represents 30 min in the real world. The case study model was simulated at the physiological scale of a human vocal fold. This simulation tracks 17 million biological cells as well as a total of 1.7 billion signaling chemical and structural protein data points. The visualization component processes and renders all simulated biological cells and 154 million signaling chemical data points. The proposed high-performance 3D ABM was verified through comparisons with empirical vocal fold data. Representative trends of biomarker predictions in surgically injured vocal folds were observed.

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Intelligent Agents and Environment

Garro¹,

Mühlhäuser²,

Tundis³

et al. 2019

Encyclopedia of Bioinformatics and Computational Biology

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Real-Time Agent-Based Modeling Simulation with in-Situ Visualization of Complex Biological Systems: A Case Study on Vocal Fold Inflammation and Healing

Cited by 8 publications

References 29 publications

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

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

High-Performance Agent-Based Modeling Applied to Vocal Fold Inflammation and Repair

Intelligent Agents and Environment

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