A Hybrid Continuous-Discrete Model of Tumour-Induced Angiogenesis is Solved Numerically in Parallel and Performance Improvements Analysed

Paul M. Darbyshire

doi:doi:10.11648/j.ejb.20150305.11

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A Hybrid Continuous-Discrete Model of Tumour-Induced Angiogenesis is Solved Numerically in Parallel and Performance Improvements Analysed

Paul M. Darbyshire

Published in European Journal of Biophysics (Volume 3, Issue 5)

Received: 30 August 2015 Accepted: 22 September 2015 Published: 13 October 2015

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Abstract

The main aim of this paper is to investigate the potential performance improvements gained from a serial versus parallel implementation of the numerical solution to a system of coupled nonlinear PDEs describing tumour-induced angiogenesis. After applying a suitable finite difference scheme, the resulting hybrid continuous discreet model is solved based on a set of cellular rules defining endothelial cell movement towards a tumour. In addition, the model explicitly incorporates the processes of branching, anastomosis and cell proliferation. Parallel implementations are based on the CUDA programming model with a detailed look at efficient thread deployment and memory management. Results show substantial speedups for the CUDA C language against that of conventional high performance languages, such as C++. Such increased performance highlights the potential for simulating more complex mathematical models of tumour dynamics, such as vascularisation networks, tumour invasion and metastasis, leading to the potential for more rapid experimental results for a range of complex cancer models.

Published in	European Journal of Biophysics (Volume 3, Issue 5)
DOI	10.11648/j.ejb.20150305.11
Page(s)	27-37
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2015. Published by Science Publishing Group

Keywords

Cancer Modelling, Tumour Angiogenic Factors (TAF), Tumour-Induced Angiogenesis, Anastomoses, Parallel Programming, Compute Unified Device Architecture (CUDA), Graphical Processing Unit (GPU), High Performance Computing (HPC)

References

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APA Style

Paul M. Darbyshire. (2015). A Hybrid Continuous-Discrete Model of Tumour-Induced Angiogenesis is Solved Numerically in Parallel and Performance Improvements Analysed. European Journal of Biophysics, 3(5), 27-37. https://doi.org/10.11648/j.ejb.20150305.11

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ACS Style

Paul M. Darbyshire. A Hybrid Continuous-Discrete Model of Tumour-Induced Angiogenesis is Solved Numerically in Parallel and Performance Improvements Analysed. Eur. J. Biophys. 2015, 3(5), 27-37. doi: 10.11648/j.ejb.20150305.11

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AMA Style

Paul M. Darbyshire. A Hybrid Continuous-Discrete Model of Tumour-Induced Angiogenesis is Solved Numerically in Parallel and Performance Improvements Analysed. Eur J Biophys. 2015;3(5):27-37. doi: 10.11648/j.ejb.20150305.11

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@article{10.11648/j.ejb.20150305.11,
  author = {Paul M. Darbyshire},
  title = {A Hybrid Continuous-Discrete Model of Tumour-Induced Angiogenesis is Solved Numerically in Parallel and Performance Improvements Analysed},
  journal = {European Journal of Biophysics},
  volume = {3},
  number = {5},
  pages = {27-37},
  doi = {10.11648/j.ejb.20150305.11},
  url = {https://doi.org/10.11648/j.ejb.20150305.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ejb.20150305.11},
  abstract = {The main aim of this paper is to investigate the potential performance improvements gained from a serial versus parallel implementation of the numerical solution to a system of coupled nonlinear PDEs describing tumour-induced angiogenesis. After applying a suitable finite difference scheme, the resulting hybrid continuous discreet model is solved based on a set of cellular rules defining endothelial cell movement towards a tumour. In addition, the model explicitly incorporates the processes of branching, anastomosis and cell proliferation. Parallel implementations are based on the CUDA programming model with a detailed look at efficient thread deployment and memory management. Results show substantial speedups for the CUDA C language against that of conventional high performance languages, such as C++. Such increased performance highlights the potential for simulating more complex mathematical models of tumour dynamics, such as vascularisation networks, tumour invasion and metastasis, leading to the potential for more rapid experimental results for a range of complex cancer models.},
 year = {2015}
}

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TY  - JOUR
T1  - A Hybrid Continuous-Discrete Model of Tumour-Induced Angiogenesis is Solved Numerically in Parallel and Performance Improvements Analysed
AU  - Paul M. Darbyshire
Y1  - 2015/10/13
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DO  - 10.11648/j.ejb.20150305.11
T2  - European Journal of Biophysics
JF  - European Journal of Biophysics
JO  - European Journal of Biophysics
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PB  - Science Publishing Group
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AB  - The main aim of this paper is to investigate the potential performance improvements gained from a serial versus parallel implementation of the numerical solution to a system of coupled nonlinear PDEs describing tumour-induced angiogenesis. After applying a suitable finite difference scheme, the resulting hybrid continuous discreet model is solved based on a set of cellular rules defining endothelial cell movement towards a tumour. In addition, the model explicitly incorporates the processes of branching, anastomosis and cell proliferation. Parallel implementations are based on the CUDA programming model with a detailed look at efficient thread deployment and memory management. Results show substantial speedups for the CUDA C language against that of conventional high performance languages, such as C++. Such increased performance highlights the potential for simulating more complex mathematical models of tumour dynamics, such as vascularisation networks, tumour invasion and metastasis, leading to the potential for more rapid experimental results for a range of complex cancer models.
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Author Information

Paul M. Darbyshire

Department of Computational Biophysics, Algenet Cancer Research, Nottingham, UK

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APA Style

Paul M. Darbyshire. (2015). A Hybrid Continuous-Discrete Model of Tumour-Induced Angiogenesis is Solved Numerically in Parallel and Performance Improvements Analysed. European Journal of Biophysics, 3(5), 27-37. https://doi.org/10.11648/j.ejb.20150305.11

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ACS Style

Paul M. Darbyshire. A Hybrid Continuous-Discrete Model of Tumour-Induced Angiogenesis is Solved Numerically in Parallel and Performance Improvements Analysed. Eur. J. Biophys. 2015, 3(5), 27-37. doi: 10.11648/j.ejb.20150305.11

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AMA Style

Paul M. Darbyshire. A Hybrid Continuous-Discrete Model of Tumour-Induced Angiogenesis is Solved Numerically in Parallel and Performance Improvements Analysed. Eur J Biophys. 2015;3(5):27-37. doi: 10.11648/j.ejb.20150305.11

Copy | Download

@article{10.11648/j.ejb.20150305.11,
  author = {Paul M. Darbyshire},
  title = {A Hybrid Continuous-Discrete Model of Tumour-Induced Angiogenesis is Solved Numerically in Parallel and Performance Improvements Analysed},
  journal = {European Journal of Biophysics},
  volume = {3},
  number = {5},
  pages = {27-37},
  doi = {10.11648/j.ejb.20150305.11},
  url = {https://doi.org/10.11648/j.ejb.20150305.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ejb.20150305.11},
  abstract = {The main aim of this paper is to investigate the potential performance improvements gained from a serial versus parallel implementation of the numerical solution to a system of coupled nonlinear PDEs describing tumour-induced angiogenesis. After applying a suitable finite difference scheme, the resulting hybrid continuous discreet model is solved based on a set of cellular rules defining endothelial cell movement towards a tumour. In addition, the model explicitly incorporates the processes of branching, anastomosis and cell proliferation. Parallel implementations are based on the CUDA programming model with a detailed look at efficient thread deployment and memory management. Results show substantial speedups for the CUDA C language against that of conventional high performance languages, such as C++. Such increased performance highlights the potential for simulating more complex mathematical models of tumour dynamics, such as vascularisation networks, tumour invasion and metastasis, leading to the potential for more rapid experimental results for a range of complex cancer models.},
 year = {2015}
}

Copy | Download

TY  - JOUR
T1  - A Hybrid Continuous-Discrete Model of Tumour-Induced Angiogenesis is Solved Numerically in Parallel and Performance Improvements Analysed
AU  - Paul M. Darbyshire
Y1  - 2015/10/13
PY  - 2015
N1  - https://doi.org/10.11648/j.ejb.20150305.11
DO  - 10.11648/j.ejb.20150305.11
T2  - European Journal of Biophysics
JF  - European Journal of Biophysics
JO  - European Journal of Biophysics
SP  - 27
EP  - 37
PB  - Science Publishing Group
SN  - 2329-1737
UR  - https://doi.org/10.11648/j.ejb.20150305.11
AB  - The main aim of this paper is to investigate the potential performance improvements gained from a serial versus parallel implementation of the numerical solution to a system of coupled nonlinear PDEs describing tumour-induced angiogenesis. After applying a suitable finite difference scheme, the resulting hybrid continuous discreet model is solved based on a set of cellular rules defining endothelial cell movement towards a tumour. In addition, the model explicitly incorporates the processes of branching, anastomosis and cell proliferation. Parallel implementations are based on the CUDA programming model with a detailed look at efficient thread deployment and memory management. Results show substantial speedups for the CUDA C language against that of conventional high performance languages, such as C++. Such increased performance highlights the potential for simulating more complex mathematical models of tumour dynamics, such as vascularisation networks, tumour invasion and metastasis, leading to the potential for more rapid experimental results for a range of complex cancer models.
VL  - 3
IS  - 5
ER  -

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