high performance computing on graphics processing units: hgpu.org

Cellular level agent based modelling is reliant on either sequential processing environments or expensive and largely unavailable PC grids. The GPU offers an alternative architecture for such systems, however the steep learning curve associated with the GPUs data parallel architecture has previously limited the uptake of this emerging technology. In this paper we demonstrate a template driven agent architecture which provides a mapping of XML model specifications and C language scripting to optimised Compute Unified Device Architecture (CUDA) for the GPU. Our work is validated though the implementation of a Keratinocyte model using limited range message communication with non linear time simulation steps to resolve inter cellular forces. The performance gain achieved over existing modelling techniques reduces simulation times from hours to seconds. The improvement of simulation performance allows us to present a real time visualisation technique which was previously unobtainable.