Learn to leverage the visualization capabilities of the NVIDIA DGX-1 system to visualize particle data. We'll cover techniques suitable for exploratory visualization such as parallel dataset reading and reduction on demand with ADIOS I/O library, GPU-based optimization techniques for particle rendering such as radar view frustum culling, occlusion culling, texture-less point sprites, and OpenGL near zero driver overhead methods. We'll also include implementation details to take advantage of the eight NVIDIA Pascal? GPUs included in the NVIDIA DGX-1.
Industry trends in the coming years in the race to exascale imply the availability of cluster computing with hundreds to thousands of cores per chip. Programming presents a challenge due to the heterogeneous architecture. Using novel programming models that facilitate this process is necessary. In this talk we present the case of simulation and visualization of crowds. We analyze and compare the use of two programming models: OmpSs and CUDA and show that OmpSs allows us to exploit all the resources combining the use of CPU and GPU taking care of memory management, scheduling, communications and synchronization automatically. We will present experimental results obtained in the Barcelona Supercomputing Center GPU Cluster as well as describe several modes used for visualizing the results.
We discuss several steps in the process for simulating and visualizing large and varied crowds, in real time, for consumer-level computers and graphic cards (GPUs). We discuss methods for simulating, generating, animating and rendering crowds of varied aspect and a diversity of behaviors.