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GPU-Based Parallelized Solver for Large Scale Vascular Blood Flow Modeling and Simulations.

Anand P Santhanam1, John Neylon1, Jeff Eldredge2

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This study introduces a GPU-accelerated solver for detailed cardiovascular blood flow simulations, enabling analysis of micro-circulation. The new method achieves high frame rates for complex vascular models.

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Area of Science:

  • Computational fluid dynamics
  • Biomedical engineering
  • Cardiovascular science

Background:

  • Cardiovascular blood flow simulations are crucial for understanding health and disease.
  • Current macro-scale simulations face computational limitations for detailed analysis.
  • Modeling micro-circulation requires advanced computational approaches.

Purpose of the Study:

  • To develop a GPU-based large-scale solver for high-resolution cardiovascular blood flow modeling.
  • To enable simulations of blood flow in the smallest arteries.
  • To analyze the impact of computational limitations on simulation scale.

Main Methods:

  • Developed a mechanical equivalent circuit-based flow modeling system.
  • Utilized a GPU computing framework for enhanced performance.
  • Employed numerical studies with 10 million connected vascular elements.

Main Results:

  • Achieved ~100 FPS on a GTX 680m GPU.
  • ~40 FPS achieved on a Tegra K1 computing platform.
  • Successfully simulated vascular blockages and arterial cut-off.

Conclusions:

  • The GPU-based solver significantly advances the scale and detail of blood flow simulations.
  • Enables high-performance analysis of complex cardiovascular dynamics.
  • Opens new possibilities for studying vascular diseases at a micro-level.