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Introducing ToPe‐FFT: An OpenCL‐based FFT library targeting GPUs
Author(s) -
Jan Bilal,
Khan Fiaz Gul,
Montrucchio Bartolomeo,
Chronopoulos Anthony Theodore,
Shamshirband Shahaboddin,
Khan Abdul Nasir
Publication year - 2017
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.4256
Subject(s) - fast fourier transform , computer science , speedup , parallel computing , computation , instruction set , factorization , computational science , algorithm
Summary In this paper, we present our implementation of the fast Fourier transforms on graphic processing unit (GPU) using OpenCL . This implementation of the FFT ( ToPe‐FFT ) is based on the Cooley‐Tukey set of algorithms with support for 1D and higher dimensional transforms using different radices. Factorization for mix‐radices enables our code to target FFTs of near arbitrary length. In systems with multiple graphic cards (GPUs), the library automatically balances the FFT computation thus achieving maximum resource utilization and higher speedup. Based on profiling and micro‐benchmarking of ToPe‐FFT , it is observed that the average speedup of our library for different sizes is 48× faster than the single CPU‐based code using FFTW and 3× faster than NVIDIA's GPU‐based cuFFT library.