Implementation of a real-time Fast Fourier Transform on a Graphics Processing Unit with data streamed from a high-performance digitizer

Abstract: In this thesis we evaluate the prospects of performing real-time digital signal processing on a graphics processing unit (GPU) when linked together with a high-performance digitizer. A graphics card is acquired and an implementation developed that address issues such as transportation of data and capability of coping with the throughput of the data stream. Furthermore, it consists of an algorithm for executing consecutive fast Fourier transforms on the digitized signal together with averaging and visualization of the output spectrum. An empirical approach has been used when researching different available options for streaming data. For better performance, an analysis of the introduced noise of using single-precision over double-precision has been performed to decide on the required precision in the context of this thesis. The choice of graphics card is based on an empirical investigation coupled with a measurement-based approach. An implementation in single-precision with streaming from the digitizer, by means of double buffering in CPU RAM, capable of speeds up to 3.0 GB/s is presented. Measurements indicate that even higher bandwidths are possible without overflowing the GPU. Tests show that the implementation is capable of computing the spectrum for transform sizes of , however measurements indicate that higher and lower transform sizes are possible. The results of the computations are visualized in real-time.