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Van Buskirk/DJB's Tangent FFT
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Date: 12 Aug 2007 16:55:34 -0000 Mail-Followup-To: [email]bnis@list.cr.yp.to[/email] Automatic-Legal-Notices: See [url]http://cr.yp.to/mailcopyright.html[/url]. From: "D. J. Bernstein" <djb@cr.yp.to> To: [email]bnis@list.cr.yp.to[/email] Subject: The tangent FFT Content-Disposition: inline If you're using the complex-floating-point split-radix FFT, you can gain a constant factor in total floating-point operations (asymptotically more than 5%!) by switching to the tangent FFT: [url]http://cr.yp.to/papers.html#tangentfft[/url] The operation count is due to Van Buskirk. The algorithm in my paper has the virtue of being simultaneously simple, in-place, and cache-friendly. I haven't seen a serious analysis of the impact of Van Buskirk's ideas for cost measures more complicated than counting arithmetic operations. The Johnson-Frigo paper on the topic claims that practical performance of FFTs is "unpredictable"; I see no justification for this claim, and my own FFT optimization experience tells me that the opposite is true. Has anyone tried a serious implementation of Van Buskirk's FFT? - ---D. J. Bernstein, Professor, Mathematics, Statistics, and Computer Science, University of Illinois at Chicago [/QUOTE] Could this be of interest for Prime95? (Note: I have not read the paper yet.) Alex |
~5.5 percent speedup in every single Lucas-Lehmering, P-1ing, ECMing, cotton-picking FFT, [I]and[/I] Bernstein's way of explaining makes me think of finally (41 years after first wondering what "Cooley-Tukey" on all those other printouts meant) plunging in to learn how FFT works!
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