Parallelizing TUNAMI-N1 Using GPGPU

We present a high performance tsunami-prediction system using General Purpose Graphics Processing Units (GPGPU). It is based on TUNAMI-N1, a Numerical Analysis Model for Investigation of near-field tsunamis. It uses linear shallow water wave equations, commonly accepted approximation for tsunami propagation, taking the input from a bathymetry file containing a large data set. Due to the largeness of the data set, the model is more amenable to parallelization. The system maps the TUNAMI-N1 model into the massively parallel GPU architecture using Nvidia CUDA framework. It employs multiple kernels that contain inherently parallel portion of the model and uses the concepts of data and hybrid parallelism to fully exploit the hardware capabilities of the GPUs. Experimental results show that our system achieves a speed up of six times.