Comparative Study of Massively Parallel GPU Realizations of Wavelet Transform Computation with Lattice Structure and Matrix-Based Approach

Dariusz Puchala, Kamil Stokfiszewski, Kamil Wieloch, Mykhaylo Yatsymirskyy
2018 2018 IEEE Second International Conference on Data Stream Mining & Processing (DSMP)  
In this paper the authors analyze the effectiveness of parallel graphics processing unit (GPU) realizations of discrete wavelet transform (DWT) using lattice structure and matrixbased approach. Experimental verification shows that, in general, for smaller input vector sizes along with the larger filter lengths DWT computation based on the direct approach with the use of the direct matrix multiplication significantly f aster t han the application of the lattice structure factorization while for
more » ... arge vector sizes the lattice structure becomes more effective. The detailed results define boundaries of performance for both implementations and determine the most advantageous situations in which one might use a given approach. The results also include comparative analysis of time efficiency o f t he p resented methods for two different GPU architectures. The presented effectiveness characteristics of the considered realizations of the two selected DWT computation methods allows for making the proper choice of the particular method in future applications depending on input data sizes, filter l engths a nd u nderlying G PU architecture.
doi:10.1109/dsmp.2018.8478567 fatcat:425k7xftpzdizlgq3vgxbzcjm4