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FFT (fast Fourier transform) plays a very important role in many fields, suchas digital signal processing, digital image processing and so on. However, inapplication, FFT becomes a factor of affecting the processing efficiency,especially in remote sensing, which large amounts of data need to be processedwith FFT. So shortening the FFT computation time is particularly important. GPU(Graphics Processing Unit) has been used in many common areas and itsacceleration effect is very obvious compared with CPU (Central Processing Unit)platform. In this paper, we present a new parallel method to execute FFT onGPU. Based on GPU storage system and hardware processing pipeline, we improvethe way of data storage. We divided the data into parts reasonably accordingthe size of data to make full use of the characteristics of the GPU. We proposethe memory optimized method based on share memory and texture memory to reducethe number of global memory access to achieve better efficiency. The resultsshow that the GPU-based memory optimized FFT implementation not only canincrease over 100% than FFTW library in CPU platform, but also can improve over30% than CUFFT library in GPU platform.

A GPU Based Memory Optimized Parallel Method For FFT Implementation