Use of GPUs to boost the performance of a lattice-free tumour growth model

Abstract

We recently developed a computational model of tumour growth. It is a cell- based model that can simulate the growth of multicellular tumour spheroids up to more than one million cells. The simulation program is very demanding and simulation time severely limits the integration of additional biological details, and indeed, at the moment, a typical simulation run requires tens of days to be completed. A new version of the code that exploits Graphics Processing Units (GPUs) to boost performance is being developed. In this paper we describe the design and implementation of a nearest-neighbour search (NNS) algorithm suitable to run on GPU. The algorithm will be integrated in the original code to manage the geometrical calculation in the simulation of the spheroid. Initially the stand alone NNS algorithm was tested for spheroids of different size: better efficency was obtained for bigger spheroids. Eventually the code was integrated in the whole simulation code and preliminary runs gave a speed up of about 5 for spheroids of relatively small size (15000 cells).