Rizzi, SilvioHereld, MarkInsley, JosephPapka, Michael E.Uram, ThomasVishwanath, VenkatramC. Dachsbacher and P. Navrátil2015-05-242015-05-242015https://doi.org/10.2312/pgv.20151149Recent large-scale particle-based simulations are generating vast amounts of data posing a challenge to visualization algorithms. One possibility for addressing this challenge is to map particles into a regular grid for volume rendering, which carries the disadvantages of inefficient use of memory and undesired losses of dynamic range. As an alternative, we propose a method to efficiently visualize these massive particle datasets using point rendering techniques with neither loss of dynamic range nor memory overheads. In addition, a hierarchical reorganization of the data is desired to deliver meaningful visual representations of a large number of particles in a limited number of pixels, preserving point locality and also helping achieve interactive frame rates. In this paper, we present a framework for parallel rendering of large-scale particle data sets combining point sprites and z-ordering. The latter is used to create a multi level representation of the data which helps improving frame rates. Performance and scalability are evaluated on a GPU-based visualization cluster, scaling up to 128 GPUs. Results using particle datasets of up to 32 billion particles are shown.I.3.2 [Computer Graphics]Graphics SystemsDistributed/network graphics10.2312/pgv.201511491-10