40 lines
2.1 KiB
Plaintext
40 lines
2.1 KiB
Plaintext
Speed:
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* If you want to use multiple cores, then compile with -openmp or -fopenmp (see your compiler docs).
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Realize that larger FFTs will reap more benefit than smaller FFTs. This generally uses more CPU time, but
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less wall time.
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* experiment with compiler flags
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Special thanks to Oscar Lesta. He suggested some compiler flags
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for gcc that make a big difference. They shave 10-15% off
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execution time on some systems. Try some combination of:
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-march=pentiumpro
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-ffast-math
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-fomit-frame-pointer
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* If the input data has no imaginary component, use the kiss_fftr code under tools/.
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Real ffts are roughly twice as fast as complex.
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* If you can rearrange your code to do 4 FFTs in parallel and you are on a recent Intel or AMD machine,
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then you might want to experiment with the USE_SIMD code. See README.simd
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Reducing code size:
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* remove some of the butterflies. There are currently butterflies optimized for radices
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2,3,4,5. It is worth mentioning that you can still use FFT sizes that contain
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other factors, they just won't be quite as fast. You can decide for yourself
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whether to keep radix 2 or 4. If you do some work in this area, let me
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know what you find.
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* For platforms where ROM/code space is more plentiful than RAM,
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consider creating a hardcoded kiss_fft_state. In other words, decide which
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FFT size(s) you want and make a structure with the correct factors and twiddles.
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* Frank van der Hulst offered numerous suggestions for smaller code size and correct operation
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on embedded targets. "I'm happy to help anyone who is trying to implement KISSFFT on a micro"
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Some of these were rolled into the mainline code base:
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- using long casts to promote intermediate results of short*short multiplication
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- delaying allocation of buffers that are sometimes unused.
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In some cases, it may be desirable to limit capability in order to better suit the target:
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- predefining the twiddle tables for the desired fft size.
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