Efficient simulation execution of cellular automata on GPU

Cagigas-Muñiz, Daniel; Díaz-del-Río, Fernando; Sevillano, José Luis; Guisado-Lizar, José-Luis

doi:10.1016/j.simpat.2022.102519

Cited by 16 publications

(4 citation statements)

References 38 publications

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“…By superimposing a grid of cells on the area of interest, the evolution of these physical processes can be reproduced. State indices and variables are attributed to cells that evolve based on transition rules [50], outperforming the standard GPU implementations, making this effective for scalability as the interactions of cells can be defined in three dimensions. Advantages over PF include being able to develop a spatial resolution by the order of magnitude of the smallest microstructure feature size [51].…”

Section: Cellular Automationmentioning

confidence: 99%

A Review of Large-Scale Simulations of Microstructural Evolution during Alloy Solidification

Cusato,

Nabavizadeh,

Eshraghi

2023

Metals

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During the past two decades, researchers have shown interest in large-scale simulations to analyze alloy solidification. Advances in in situ X-ray observations of the microstructural evolution of dendrites have shown defects that can be very costly for manufacturers. These simulations provide the basis for understanding applied meso-/macro-scale phenomena with microscale details using various numerical schemes to simulate the morphology and solve for transport phenomena. Methods for simulating methodologies include cellular automaton, phase field, direct interface tracking, level set, dendritic needle networks, and Monte Carlo while finite element, finite difference, finite volume, and lattice Boltzmann methods are commonly used to solve for transport phenomena. In this paper, these methodologies are explored in detail with respect to simulating the dendritic microstructure evolution and other solidification-related features. The current research, from innovations in algorithms for scaling to parallel processing details, is presented with a focus on understanding complex real-world phenomena. Topics include large-scale simulations of features with and without convection, columnar to equiaxed transition, dendrite interactions, competitive growth, microsegregation, permeability, and applications such as additive manufacturing. This review provides the framework and methodologies for achieving scalability while highlighting the areas of focus that need more attention.

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Section: Cellular Automationmentioning

confidence: 99%

A Review of Large-Scale Simulations of Microstructural Evolution during Alloy Solidification

Cusato,

Nabavizadeh,

Eshraghi

2023

Metals

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“…For this type of simulation, it is extremely important to effectively manage memory bandwidth, which is one of the limitations of GPU programming. An interesting analysis of this issue is presented, [ 162 ] where special code optimizations based on elements such as stencil computing framework, look‐up tables, and packet coding to properly take into account the detailed architecture are considered.…”

Section: High‐performance Ca Models Of Static Recrystallizationmentioning

confidence: 99%

Computationally Efficient Cellular Automata‐Based Full‐Field Models of Static Recrystallization: A Perspective Review

Madej

Sitko

2022

steel research int.

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The evolution of metallic material microstructures under thermomechanical treatment is a critical element that influences the in‐use properties of the final product. In the last four decades, many researchers around the world focused on reliable numerical recreation of phenomena that occur during metal processing. Particular attention is put on the phase transformation, texture evolution, and recrystallization predictions to simulate material behavior at the subsequent processing stages. In recent years, approaches taking into account explicit representation of morphological elements during simulation are becoming more frequently used even at the industrial scale. One of those methods addressed within the current article in application to static recrystallization (SRX) modeling is the cellular automata (CA) approach. A review of the CA‐based full‐field SRX models highlights the progress in capabilities of developed approaches in consideration of various mechanisms controlling microstructure evolution like heterogeneous energy distribution, probabilistic or physics‐based nucleation, grain growth driven by different driving forces, or grain boundary migration is presented within the article. The issue of the computational time associated with 3D CA modeling is particularly addressed. Possible approaches to reducing simulation times based on efficient use of modern computer architecture are finally evaluated as guidelines for further model development.

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“…Sussman 16 considered a vertex model approach through the cellGPU package aiming to efficiently compute the evolution of cell shape in connected tissues. Meanwhile, Cagigas-Muniz et al 17 used a CA model to demonstrate GPU acceleration techniques with Jelinek et al 18 applying a different CA model to simulate dendrite growth. Centre-based modelling approaches have been used to produce a high performance model specific to epithelial tissue morphogenesis 19 .…”

Section: Introductionmentioning

confidence: 99%

BMX: Biological modelling and interface exchange

Palmer

Almgren

Johnson

et al. 2023

Sci Rep

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High performance computing has a great potential to provide a range of significant benefits for investigating biological systems. These systems often present large modelling problems with many coupled subsystems, such as when studying colonies of bacteria cells. The aim to understand cell colonies has generated substantial interest as they can have strong economic and societal impacts through their roles in in industrial bioreactors and complex community structures, called biofilms, found in clinical settings. Investigating these communities through realistic models can rapidly exceed the capabilities of current serial software. Here, we introduce BMX, a software system developed for the high performance modelling of large cell communities by utilising GPU acceleration. BMX builds upon the AMRex adaptive mesh refinement package to efficiently model cell colony formation under realistic laboratory conditions. Using simple test scenarios with varying nutrient availability, we show that BMX is capable of correctly reproducing observed behavior of bacterial colonies on realistic time scales demonstrating a potential application of high performance computing to colony modelling. The open source software is available from the zenodo repository https://doi.org/10.5281/zenodo.8084270 under the BSD-2-Clause licence.

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Efficient simulation execution of cellular automata on GPU

Cited by 16 publications

References 38 publications

A Review of Large-Scale Simulations of Microstructural Evolution during Alloy Solidification

A Review of Large-Scale Simulations of Microstructural Evolution during Alloy Solidification

Computationally Efficient Cellular Automata‐Based Full‐Field Models of Static Recrystallization: A Perspective Review

BMX: Biological modelling and interface exchange

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