Abstract
Computing ”in-place and in-order” FFT poses a very difficult problem on hierarchical memory architectures where data movement can seriously degrade the performance. In this paper we present recursive formulation of a self sorting in-place FFT algorithm that adapts to the target architecture. For transform sizes where an in-place, in-order execution is not possible, we show how schedules can be constructed that use minimum work-space to perform the computation efficiently. In order to express and construct FFT schedules, we present a context free grammar that generates the FFT Schedule Specification Language. We conclude by comparing the performance of our in-place in-order FFT implementation with that of other well known FFT libraries. We also present a performance comparison between the out-of-place and in-place execution of various FFT sizes.
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Ali, A., Johnsson, L., Subhlok, J. (2007). Adaptive Computation of Self Sorting In-Place FFTs on Hierarchical Memory Architectures. In: Perrott, R., Chapman, B.M., Subhlok, J., de Mello, R.F., Yang, L.T. (eds) High Performance Computing and Communications. HPCC 2007. Lecture Notes in Computer Science, vol 4782. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75444-2_38
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DOI: https://doi.org/10.1007/978-3-540-75444-2_38
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-75443-5
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