A highly accurate software scanned cell projection algorithm and its parallelization

We develop a highly accurate software scanned cell projection algorithm which is applicable of any classification system. This algorithm could handle both convex and non-convex meshes, and provide maximum flexibilities in applicable types of cells. Compared with previous algorithms using 3D commodity graphics hardware, it introduces no the volume decomposition and rendering artifacts in the resulting images. Furthermore, its parallel version is investigated to overcome the bottleneck of the serial one in terms of time and memory consuming for visualizing large scale unstructured data. Finally, high resolution images generated by the parallel algorithm are provided, and the scalability of the algorithm is demonstrated on a PC Cluster with modest parallel resources.