Parallelizing the cellular potts model on GPU and multi-core CPU: An OpenCL cross-platform study

Yu, Chao; Yang, Bo

doi:10.1109/jcsse.2014.6841853

Cited by 4 publications

(4 citation statements)

References 13 publications

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“…Agent-based approaches often lend themselves to parallelization-for example, the following models that were mentioned in the introduction (Richmond et al, 2010;Tapia and D'Souza, 2011;Gord et al, 2014;Yu and Yang, 2014;Cytowski and Szymanska, 2015;Harvey et al, 2015;Ballet, 2018;Ghaffarizadeh et al, 2018;Song et al, 2018). For high performance at low costs, we implemented our models into a GPU-based simulation framework.…”

Section: Discussionmentioning

confidence: 99%

“…As the correct biological mechanism is often not known or very complex, the development of phenomenological models and the exploration of their parameter space require flexible and efficient simulation frameworks. However, previous simulation frameworks for morphogenesis (Hoehme and Drasdo, 2010;Richmond et al, 2010;Tapia and D'Souza, 2011;Gorochowski et al, 2012;Rudge et al, 2012;Swat et al, 2012;Mirams et al, 2013;S€ utterlin et al, 2013;Gord et al, 2014;Kang et al, 2014;Starruß et al, 2014;Yu and Yang, 2014;Cytowski and Szymanska, 2015;Barton et al, 2017;Somogyi and Glazier, 2017;Sussman, 2017;Ballet, 2018;Ghaffarizadeh et al, 2018;Song et al, 2018) often emphasized either epithelial or mesenchymal processes, e.g., vertex models describe the shapes of epithelial cells within sheets or cellular Potts models describe differential adhesion (Osborne et al, 2017). Recently, solutions to overcome this limitation were put forward: an extension of the spheroid model by torsion joints (Disset et al, 2015), a 3D implementation of the vertex model (Okuda et al, 2015), a sub-cellular element model using apical and basal elements for epithelial cells (Gord et al, 2014), a sub-cellular element model using cylindrical elements for epithelial cells (Marin-Riera et al, 2016), and most recently a spheroid model with apical-basal polarity (Delile et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

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ya||a: GPU-Powered Spheroid Models for Mesenchyme and Epithelium

2019

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

ya||a: GPU-Powered Spheroid Models for Mesenchyme and Epithelium

2019

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“…To reach optimal speedup, GPUs rely heavily on the synchronicity and the locality of the algorithm. Although GPU-implementations of the CPM have been proposed [90,98], a fully synchronous, local reformulation of the CPM would help dramatically speedup CPM-simulations.…”

Section: Discussionmentioning

confidence: 99%

Cellular Potts Model: Applications to Vasculogenesis and Angiogenesis

Boas

Jiang

Merks

et al. 2018

Emergence, Complexity and Computation

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License: Article 25fa pilot End User AgreementThis publication is distributed under the terms of Article 25fa of the Dutch Copyright Act (Auteurswet) with explicit consent by the author. Dutch law entitles the maker of a short scientific work funded either wholly or partially by Dutch public funds to make that work publicly available for no consideration following a reasonable period of time after the work was first published, provided that clear reference is made to the source of the first publication of the work.This publication is distributed under The Association of Universities in the Netherlands (VSNU) 'Article 25fa implementation' pilot project. In this pilot research outputs of researchers employed by Dutch Universities that comply with the legal requirements of Article 25fa of the Dutch Copyright Act are distributed online and free of cost or other barriers in institutional repositories. Research outputs are distributed six months after their first online publication in the original published version and with proper attribution to the source of the original publication.You are permitted to download and use the publication for personal purposes. All rights remain with the author(s) and/or copyrights owner(s) of this work. Any use of the publication other than authorised under this licence or copyright law is prohibited.If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website.

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“…Tapia and D'Souza [10,11] use this method to implement a single Graphics Processing Unit (GPU) version. Yu and Yang [12] use OpenCL to execute their model on GPUs and multi-core Compute Processing Units (CPUs).…”

Section: Related Workmentioning

confidence: 99%

Cells in Silico – introducing a high-performance framework for large-scale tissue modeling

et al. 2020

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Background Discoveries in cellular dynamics and tissue development constantly reshape our understanding of fundamental biological processes such as embryogenesis, wound-healing, and tumorigenesis. High-quality microscopy data and ever-improving understanding of single-cell effects rapidly accelerate new discoveries. Still, many computational models either describe few cells highly detailed or larger cell ensembles and tissues more coarsely. Here, we connect these two scales in a joint theoretical model. Results We developed a highly parallel version of the cellular Potts model that can be flexibly applied and provides an agent-based model driving cellular events. The model can be modular extended to a multi-model simulation on both scales. Based on the NAStJA framework, a scaling implementation running efficiently on high-performance computing systems was realized. We demonstrate independence of bias in our approach as well as excellent scaling behavior. Conclusions Our model scales approximately linear beyond 10,000 cores and thus enables the simulation of large-scale three-dimensional tissues only confined by available computational resources. The strict modular design allows arbitrary models to be configured flexibly and enables applications in a wide range of research questions. Cells in Silico (CiS) can be easily molded to different model assumptions and help push computational scientists to expand their simulations to a new area in tissue simulations. As an example we highlight a 10003 voxel-sized cancerous tissue simulation at sub-cellular resolution.

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Parallelizing the cellular potts model on GPU and multi-core CPU: An OpenCL cross-platform study

Cited by 4 publications

References 13 publications

ya||a: GPU-Powered Spheroid Models for Mesenchyme and Epithelium

ya||a: GPU-Powered Spheroid Models for Mesenchyme and Epithelium

Cellular Potts Model: Applications to Vasculogenesis and Angiogenesis

Cells in Silico – introducing a high-performance framework for large-scale tissue modeling

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