Development and performance of a HemeLB GPU code for human-scale blood flow simulation

Zacharoudiou, Ioannis; McCullough, J. W. S.; Coveney, Peter V.

doi:10.1016/j.cpc.2022.108548

Cited by 3 publications

(2 citation statements)

References 61 publications

(93 reference statements)

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“…For example, the HemeLB solver, which is based on the lattice Boltzmann method, is widely utilized for simulating blood flow using real patient images. Zacharoudiou et al (2023) [8] utilized the method's strong scaling capability to adapt their algorithm for execution on a GPU architecture using CUDA-C language. Indeed, such scalability extends to a higher level of parallelism for GPU codes compared to CPU codes.…”

Section: Introductionmentioning

confidence: 99%

An Implementation of LASER Beam Welding Simulation on Graphics Processing Unit Using CUDA

Nascimento,

Magalhães,

Azevedo

et al. 2024

Computation

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The maximum number of parallel threads in traditional CFD solutions is limited by the Central Processing Unit (CPU) capacity, which is lower than the capabilities of a modern Graphics Processing Unit (GPU). In this context, the GPU allows for simultaneous processing of several parallel threads with double-precision floating-point formatting. The present study was focused on evaluating the advantages and drawbacks of implementing LASER Beam Welding (LBW) simulations using the CUDA platform. The performance of the developed code was compared to that of three top-rated commercial codes executed on the CPU. The unsteady three-dimensional heat conduction Partial Differential Equation (PDE) was discretized in space and time using the Finite Volume Method (FVM). The Volumetric Thermal Capacitor (VTC) approach was employed to model the melting-solidification. The GPU solutions were computed using a CUDA-C language in-house code, running on a Gigabyte Nvidia GeForce RTX™ 3090 video card and an MSI 4090 video card (both made in Hsinchu, Taiwan), each with 24 GB of memory. The commercial solutions were executed on an Intel® Core™ i9-12900KF CPU (made in Hillsboro, Oregon, United States of America) with a 3.6 GHz base clock and 16 cores. The results demonstrated that GPU and CPU processing achieve similar precision, but the GPU solution exhibited significantly faster speeds and greater power efficiency, resulting in speed-ups ranging from 75.6 to 1351.2 times compared to the CPU solutions. The in-house code also demonstrated optimized memory usage, with an average of 3.86 times less RAM utilization. Therefore, adopting parallelized algorithms run on GPU can lead to reduced CFD computational costs compared to traditional codes while maintaining high accuracy.

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Section: Introductionmentioning

confidence: 99%

An Implementation of LASER Beam Welding Simulation on Graphics Processing Unit Using CUDA

Nascimento,

Magalhães,

Azevedo

et al. 2024

Computation

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“…Computational fluid dynamics (CFD) is useful for studying these effects as it allows non-invasive analysis of blood flow in various settings [18]. The lattice Boltzmann method (LBM) [19,20] is attractive for the simulation of blood flow since it is applicable to complex geometries and highly scalable on supercomputers [21][22][23]. Previous works have used LBM in modelling the effects of the wall motion [24,25], blood rheology [26,27] and pulsatile blood flow [26,28].…”

Section: Introductionmentioning

confidence: 99%

Uncertainty quantification of the impact of peripheral arterial disease on abdominal aortic aneurysms in blood flow simulations

Lo,

McCullough,

Xue

et al. 2024

J. R. Soc. Interface.

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Peripheral arterial disease (PAD) and abdominal aortic aneurysms (AAAs) often coexist and pose significant risks of mortality, yet their mutual interactions remain largely unexplored. Here, we introduce a fluid mechanics model designed to simulate the haemodynamic impact of PAD on AAA-associated risk factors. Our focus lies on quantifying the uncertainty inherent in controlling the flow rates within PAD-affected vessels and predicting AAA risk factors derived from wall shear stress. We perform a sensitivity analysis on nine critical model parameters through simulations of three-dimensional blood flow within a comprehensive arterial geometry. Our results show effective control of the flow rates using two-element Windkessel models, although specific outlets need attention. Quantities of interest like endothelial cell activation potential (ECAP) and relative residence time are instructive for identifying high-risk regions, with ECAP showing greater reliability and adaptability. Our analysis reveals that the uncertainty in the quantities of interest is 187% of that of the input parameters. Notably, parameters governing the amplitude and frequency of the inlet velocity exert the strongest influence on the risk factors’ variability and warrant precise determination. This study forms the foundation for patient-specific simulations involving PAD and AAAs which should ultimately improve patient outcomes and reduce associated mortality rates.

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The Lattice Boltzmann Based Large Eddy Simulations for the Stenosis of the Aorta

Xue,

McCullough,

et al. 2024

Lecture Notes in Computer Science

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Development and performance of a HemeLB GPU code for human-scale blood flow simulation

Cited by 3 publications

References 61 publications

An Implementation of LASER Beam Welding Simulation on Graphics Processing Unit Using CUDA

An Implementation of LASER Beam Welding Simulation on Graphics Processing Unit Using CUDA

Uncertainty quantification of the impact of peripheral arterial disease on abdominal aortic aneurysms in blood flow simulations

The Lattice Boltzmann Based Large Eddy Simulations for the Stenosis of the Aorta

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