Parallel Implementation of the 2D Discrete Wavelet Transform on Graphics Processing Units: Filter Bank versus Lifting

February 11th, 2008

Abstract: “The widespread usage of the Discrete Wavelet Transform (DWT) has motivated the development of fast DWT algorithms and their tuning on all sorts of computer systems. Several studies have compared the performance of the most popular schemes, known as Filter Bank (FBS) and Lifting (LS), and have always concluded that Lifting is the most efficient option. However, there is no such study on streaming processors such as modern Graphic Processing Units (GPUs). Current trends have transformed these devices into powerful stream processors with enough flexibility to perform intensive and complex floating-point calculations. The opportunities opened up by these platforms, as well as the growing popularity of the DWT within the computer graphics field, make a new performance comparison of great practical interest. Our study indicates that FBS outperforms LS in current generation GPUs. In our experiments, the actual FBS gains range between 10% and 140%, depending on the problem size and the type and length of the wavelet filter. Moreover, design trends suggest higher gains in future generation GPUs. (Parallel Implementation of the 2D Discrete Wavelet Transform on Graphics Processing Units: Filter Bank versus Lifting. Christian Tenllado, Javier Setoain, Manuel Prieto, Luis Piñuel, and Francisco Tirado. IEEE Transactions on Parallel and Distributed Systems ,vol. 19, no. 3, pp. 299-310, March, 2008. )