#Cuda dim3 3dimension compute 5.0 update#

In this paper, the authors develop the algorithm further and utilise the graphical interoperability available on parallel platforms to visualise the angiogenetic process in 3D. Whilst also highlighting the many optimisation techniques available to further improve the performance of the algorithm. The numerical solution was implemented on the GPU and results indicated an impressive increase in execution time over that of a conventional C++ algorithm. In a previous paper, the authors developed a 3D parallel algorithm based on a time-stepping finite difference method (FDM) to solve a hybrid continuous-discrete model of tumour-induced angiogenesis. More recently, the advantages of supercomputing and parallel processing techniques has highlighted the speedup, amongst other benefits, from the numerical solution of complex mathematical models of tumour dynamics. With such a predictive model it is much easier and faster to perform in silico experiments to test hypotheses and predictions than running time consuming and costly laboratory experiments. Once we have a model that is validated it is possible to more efficiently predict what should be happening in a particular experiment. Such in silico experiments focussed on the dynamics of tumour growth and other related biological phenomenon have become readily accepted by the scientific community both as a means to direct new research and a route to generate new hypotheses and testable predictions.

Over the last decade, high-performance computing has evolved dramatically, in particular because of the accessibility to graphics processing units (GPUs) and the emergence of GPU-CPU heterogeneous architectures, which have led to a huge shift in the available medical applications for supercomputing and parallel programming.

Keywords: 3D Cancer Modelling, 3D Visualisation, Medical Imaging, High Performance Computing,Ĭompute Unified Device Architecture (CUDA), Graphical Processing Unit (GPU), We also give an overview of current medical imaging techniques for studying microcirculatory and blood flow dynamics at the cellular level and indicate how the results presented here could offer potential for future developments in this area.

#Cuda dim3 3dimension compute 5.0 update#

Clearly, being able to link the numerical results of complex mathematical models to interactive 3D visualisations that can literally update instantaneously to varying model parameters, should provide an invaluable tool for clinical physicians and research scientists. We use CUDA for the complex parallel calculations and deploy OpenGL for on-the-fly 3D visualisation of the numerical simulations. The interoperability between the CUDA programming model and the graphics hardware through OpenGL allows us to generate dynamic interactive 3D realistic visualisations. Abstract: In this paper we solve a complex discrete-continuous model of tumour-induced angiogenesis using an explicit time-stepping FDM and simultaneously simulate the model dynamics in 3D.