Towards a large-scale scalable adaptive heart model using shallow tree meshes

Krause, Dorian; Dickopf, Thomas; Potse, Mark; Krause, Rolf

doi:10.1016/j.jcp.2015.05.005

Cited by 14 publications

(12 citation statements)

References 31 publications

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“…Several groups around the world [142,212,243,260] are using massively parallel computing and especially graphics processing units to speed up the computations in realistic heart geometries using highly-detailed physiological electrophysiology models, with the ultimate goal of providing near realtime simulations. Alternatively, other efforts point to reducing the complexity of the underlying cellular models [126].…”

Section: Discussionmentioning

confidence: 99%

Integrated Heart—Coupling multiscale and multiphysics models for the simulation of the cardiac function

Quarteroni

Lassila

Rossi

et al. 2017

Computer Methods in Applied Mechanics and Engineering

208

205

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Section: Discussionmentioning

confidence: 99%

Integrated Heart—Coupling multiscale and multiphysics models for the simulation of the cardiac function

Quarteroni

Lassila

Rossi

et al. 2017

Computer Methods in Applied Mechanics and Engineering

208

205

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“…The work presented in Cristoforetti et al uses an adaptive mesh algorithm, based on multiresolution representation and unstructured triangular meshes. In Krause et al, a parallel algorithm in distributed memory is presented that uses a new spatially adaptive scheme, combining the advantages of structured meshes, and a low memory footprint. Finally, in Ying and Henriquez, the authors presented a space and time adaptive algorithm for simulating electrical wave propagation in the Purkinje system of the heart with a speedup of 15×.…”

Section: Discussionmentioning

confidence: 99%

Performance evaluation of GPU parallelization, space‐time adaptive algorithms, and their combination for simulating cardiac electrophysiology

Oliveira

Rocha

Burgarelli

et al. 2017

Numer Methods Biomed Eng

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The use of computer models as a tool for the study and understanding of the complex phenomena of cardiac electrophysiology has attained increased importance nowadays. At the same time, the increased complexity of the biophysical processes translates into complex computational and mathematical models. To speed up cardiac simulations and to allow more precise and realistic uses, 2 different techniques have been traditionally exploited: parallel computing and sophisticated numerical methods. In this work, we combine a modern parallel computing technique based on multicore and graphics processing units (GPUs) and a sophisticated numerical method based on a new space-time adaptive algorithm. We evaluate each technique alone and in different combinations: multicore and GPU, multicore and GPU and space adaptivity, multicore and GPU and space adaptivity and time adaptivity. All the techniques and combinations were evaluated under different scenarios: 3D simulations on slabs, 3D simulations on a ventricular mouse mesh, ie, complex geometry, sinus-rhythm, and arrhythmic conditions. Our results suggest that multicore and GPU accelerate the simulations by an approximate factor of 33×, whereas the speedups attained by the space-time adaptive algorithms were approximately 48. Nevertheless, by combining all the techniques, we obtained speedups that ranged between 165 and 498. The tested methods were able to reduce the execution time of a simulation by more than 498× for a complex cellular model in a slab geometry and by 165× in a realistic heart geometry simulating spiral waves. The proposed methods will allow faster and more realistic simulations in a feasible time with no significant loss of accuracy.

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“…In the context of fast solution methods, Mortar methods have also been used to derive adaptive space-time discretization methods, see [51,50], which combine the advantages of structured meshes in terms of simple data-structures with the advantages of adaptive discretizations. Figure 2 shows the mesh hierarchy for simulated electric potential in a human heart.…”

Section: Coupled Simulations With Mortar Methods In Hpcmentioning

confidence: 99%

Frontiers in Mortar Methods for Isogeometric Analysis

Hesch¹,

Khristenko²,

Krause³

et al. 2020

Preprint

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Complex geometries as common in industrial applications consist of multiple patches, if spline based parametrizations are used. The requirements for the generation of analysis-suitable models are increasing dramatically since isogeometric analysis is directly based on the spline parametrization and nowadays used for the calculation of higher-order partial differential equations. The computational, or more general, the engineering analysis necessitates suitable coupling techniques between the different patches. Mortar methods have been successfully applied for coupling of patches and for contact mechanics in recent years to resolve the arising issues within the interface. We present here current achievements in the design of mortar technologies in isogeometric analysis within the Priority Program SPP 1748, Reliable Sim-

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Towards a large-scale scalable adaptive heart model using shallow tree meshes

Cited by 14 publications

References 31 publications

Integrated Heart—Coupling multiscale and multiphysics models for the simulation of the cardiac function

Integrated Heart—Coupling multiscale and multiphysics models for the simulation of the cardiac function

Performance evaluation of GPU parallelization, space‐time adaptive algorithms, and their combination for simulating cardiac electrophysiology

Frontiers in Mortar Methods for Isogeometric Analysis

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