ArticleJournal of computational science2020
Multi-GPU Immersed Boundary Method Hemodynamics Simulations.
Article in Journal of computational science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Accelerated Method for Simulating the Solidification Microstructure of Continuous Casting Billets on GPUs.Materials (Basel, Switzerland) · 2025Article
- A Python-based flow solver for numerical simulations using an immersed boundary method on single GPUs.Computers & fluids · 2025Article
- Establishing the longitudinal hemodynamic mapping framework for wearable-driven coronary digital twins.NPJ digital medicine · 2024Article
- A cell-and-plasma numerical model reveals hemodynamic stress and flow adaptation in zebrafish microvessels after morphological alteration.PLoS computational biology · 2023Article
- Enhancing Adaptive Physics Refinement Simulations Through the Addition of Realistic Red Blood Cell Counts.International Conference for High Performance Computing, Networking, Storage and Analysis : [proceedings]. SC (Conference : Supercomputing) · 2023Article
- Cloud Computing to Enable Wearable-Driven Longitudinal Hemodynamic Maps.International Conference for High Performance Computing, Networking, Storage and Analysis : [proceedings]. SC (Conference : Supercomputing) · 2023Article
- Modeling Dynamics of the Cardiovascular System Using Fluid-Structure Interaction Methods.Biology · 2023Review
- Effect of constitutive law on the erythrocyte membrane response to large strains.Computers & mathematics with applications (Oxford, England : 1987) · 2023Article
- Red blood cell dynamics in extravascular biological tissues modelled as canonical disordered porous media.Interface focus · 2022Article
- Distributed Acceleration of Adhesive Dynamics Simulations.Proceedings of 2022 29th European MPI Users' Group Meeting (EuroMPI/USA'2022) : September 26-28, 2022, Chattanooga, TN. European MPI Users' Group Meeting (29th : 2022 : Chattanooga, Tenn.) · 2022Article
- High Performance Adaptive Physics Refinement to Enable Large-Scale Tracking of Cancer Cell Trajectory.Proceedings. IEEE International Conference on Cluster Computing · 2022Article
- The role of adhesive receptor patterns on cell transport in complex microvessels.Biomechanics and modeling in mechanobiology · 2022Article
- Computational Science in the Interconnected World: Selected papers from 2019 International Conference on Computational Science.Journal of computational science · 2020Article
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6 authors.
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Abstract
Large-scale simulations of blood flow that resolve the 3D deformation of each comprising cell are increasingly popular owing to algorithmic developments in conjunction with advances in compute capability. Among different approaches for modeling cell-resolved hemodynamics, fluid structure interaction (FSI) algorithms based on the immersed boundary method are frequently employed for coupling separate solvers for the background fluid and the cells within one framework. GPUs can accelerate these simulations; however, both current pre-exascale and future exascale CPU-GPU heterogeneous systems face communication challenges critical to performance and scalability. We describe, to our knowledge, the largest distributed GPU-accelerated FSI simulations of high hematocrit cell-resolved flows with over 17 million red blood cells. We compare scaling on a fat node system with six GPUs per node and on a system with a single GPU per node. Through comparison between the CPU- and GPU-based implementations, we identify the costs of data movement in multiscale multi-grid FSI simulations on heterogeneous systems and show it to be the greatest performance bottleneck on the GPU.
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