Scientic Computation for Simulations on Programmable Graphics Hardware

Graphics Processor Units (GPUs) have emerged as powerful parallel processors in recent years. Although oating point computations and high level programming languages are now available, the efcient use of the enormous computing power of GPUs still requires a signicant amount of graphics specic knowledge. The paper explains how to use GPUs for scientic computations without graphics spe-cic terminology. It offers an algorithmic view on GPUs with comparisons to cache aware and parallel programming of CPUs. Two typical simulation techniques, namely grid based and particle based methods are discussed.