Abstract
Modern graphics processing units (GPU) are becoming more and more suitable for general purpose computing due to its growing computational power. These commodity processors follow, in general, a parallel SIMD execution model whose efficiency is subject to a right exploitation of the explicit memory hierarchy, among other factors. In this paper we analyze the implementation of the Fast Fourier Transform using the programming model of the Compute Unified Device Architecture (CUDA) recently released by NVIDIA for its new graphics platforms. Within this model we propose an FFT implementation that takes into account memory reference locality issues that are crucial in order to achieve a high execution performance. This proposal has been experimentally tested and compared with other well known approaches such as the manufacturer’s FFT library.
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© 2008 Springer-Verlag Berlin Heidelberg
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Gutierrez, E., Romero, S., Trenas, M.A., Zapata, E.L. (2008). Memory Locality Exploitation Strategies for FFT on the CUDA Architecture. In: Palma, J.M.L.M., Amestoy, P.R., Daydé, M., Mattoso, M., Lopes, J.C. (eds) High Performance Computing for Computational Science - VECPAR 2008. VECPAR 2008. Lecture Notes in Computer Science, vol 5336. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92859-1_39
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DOI: https://doi.org/10.1007/978-3-540-92859-1_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-92858-4
Online ISBN: 978-3-540-92859-1
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