High-speed parallel wavelet algorithm based on CUDA and its application in power system harmonic analysis

As there is few applications of wavelet decomposition in actual engineering because of its low calculation speed,a fine-grained parallel wavelet decomposition algorithm based on CUDA(Compute Unified Device Architecture) is proposed,which takes the GPU(Graphic Processing Unit) as platform.The parallelity of the Mallat algorithm is analyzed.With the consideration of the poor performance of GPU processor and the CUDA framework of multilevel memory,multilevel thread organization and SIMT(Single-Instruction,Multiple-Thread),high-speed parallel wavelet decomposition algorithm is proposed for power system harmonic analysis,which applies the methodology of data grouping and lightweight thread task decomposing,suitable for the CUDA programming model.Experiments show that,the calculation speed is 26 times and 65 times faster compared with that of CPU serial wavelet decomposition and Matlab engine wavelet decomposition respectively,and the algorithm has the linear speedup capability.