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Parallel implementation of Fast Fourier Transform in Spherical Coordinates. Mentor: Dr.Luis Cueva-Parra Intern: Adrian Rodriguez. Outline. My project How it is done today My new approach Impact Timeline Benchmarks. The Project. Description. What I am trying to do.
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Parallel implementation of Fast Fourier Transform in Spherical Coordinates Mentor: Dr.Luis Cueva-Parra Intern: Adrian Rodriguez
Outline • My project • How it is done today • My new approach • Impact • Timeline • Benchmarks
The Project Description What I am trying to do • Fast Fourier Transforms are computed every day all around us for signal processing , Medical imaging. Also applied to compute mathematics in Quantum Physics • I will be attempting to parallelize the Fast Fourier Transform algorithm and have it perform the computation corresponding to spherical coordinates, as opposed to cartesian.
How it is done today • FFTW is a C subroutine library for computing the discrete Fourier transform (DFT) in one or more dimensions. • FFTW does have a working library for multidimensional FFT’s for shared memory, and distributed memory.
My approach • I won’t be redeveloping the library • I will be creating a subroutine to run FFT’s using a hybrid approach by implementing MPI, and OpenMP • I will also create a subroutine to implement FFT’s in spherical coordinates • It may be easier to compute.
Impact • Improving efficiency in electrical systems by predicting the electron flow in different mediums.
Timeline Important: Document everything
Benchmark • What is success: • Code executes arithmetic correctly • Code runs faster in parallel than in serial • Met required time frames • How will I measure it? • Analyze output data with known outputs • get_wtime to output run time. Compare to serial version • Finish