WSJT-X/lib/chkfft.txt
Joe Taylor ccba704126 A few more tweaks, and add the file nfft.dat of efficient FFT lengths.
git-svn-id: svn+ssh://svn.code.sf.net/p/wsjt/wsjt/branches/wsjtx@4837 ab8295b8-cf94-4d9e-aec4-7959e3be5d79
2014-12-18 20:53:16 +00:00

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Brief Description of chkfft, by K1JT
------------------------------------
Discrete Fourier transforms (DFTs) are found at the root of most
digital signal processing tasks. In WSJT and its sister programs the
transforms are done using the FFTW library, and subroutine four2
provides a convenient interface to the library. Program chkfft is a
command-line utility offering a convenient way to test FFT execution
times under a variety of circumstances.
To compile chkfft in Linux:
$ gfortran -o chkfft chkfft.f90 four2a.f90 f77_wisdom.f90 gran.c -lfftw3f
To compile chkfft in Windows (you may need to customize the hard-coded
path shown here for libfftw3f-3.dll):
> gfortran -o chkfft chkfft.f90 four2a.f90 f77_wisdom.f90 gran.c \
/JTSDK-QT/appsupport/runtime/libfftw3f-3.dll
To see a brief usage message, type chkfft at the command prompt:
$ chkfft
Usage: chkfft <nfft | infile> nr nw nc np
nfft: length of FFT
nfft=0: do lengths 2^n, n=2^4 to 2^23
infile: name of file with nfft values, one per line
nr: 0/1 to not read (or read) wisdom
nw: 0/1 to not write (or write) wisdom
nc: 0/1 for real or complex data
np: 0-4 patience for finding best algorithm
As an example, to measure the speed of a complex DFT of length 131072:
#######################################################################
$ chkfft 131072 0 1 1 2
nfft: 131072 nr: 0 nw 1 nc: 1 np: 2
NFFT Time rms MHz MFlops iters tplan
-------------------------------------------------------------
131072 0.0021948 0.00000032 59.72 5076.1 231 2.9
#######################################################################
Program output shows that on the test machine the average time for one
forward (or inverse) transform of length N=131072 is about 2.2 ms,
corresponding to slightly over 5 GFlops computing speed. The planning
time in FFTW was 2.9 s.
Running the command again with parameter nr=1 will use the
"wisdom" already accumulated for complex N=131072 FFTs. The execution
speed will be essentially the same, but no planning time is required:
#######################################################################
$ chkfft 131072 1 1 1 2
nfft: 131072 nr: 1 nw 1 nc: 1 np: 2
NFFT Time rms MHz MFlops iters tplan
-------------------------------------------------------------
131072 0.0021575 0.00000032 60.75 5164.0 235 0.0
#######################################################################
Optimized algorithms can compute DFTs much faster for lengths that are
the product of small integers. Length N=131072 = 2^17 is a good
example, and FFTs should be very efficient. For comparison, look at
the speed for N=131071, a prime number. The average time is now about
7 times larger:
#######################################################################
C:\JTSDK-QT\src\wsjtx\lib>chkfft 131071 1 1 1 2
nfft: 131071 nr: 1 nw 1 nc: 1 np: 2
NFFT Time rms MHz MFlops iters tplan
-------------------------------------------------------------
131071 0.0153637 0.00000065 8.53 725.2 33 5.6
#######################################################################
Here's an example that measures execution times for all integral
power-of-2 lengths from 2^4 to 2^23:
#######################################################################
$ chkfft 0 1 1 1 2
nfft: 0 nr: 1 nw 1 nc: 1 np: 2
n N=2^n Time rms MHz MFlops iters tplan
---------------------------------------------------------------
4 16 0.0000003 0.00000014 58.61 1172.2 1000000 0.0
5 32 0.0000004 0.00000016 89.19 2229.6 1000000 0.0
6 64 0.0000006 0.00000016 109.44 3283.2 866975 0.0
7 128 0.0000009 0.00000021 135.92 4757.1 538369 0.0
8 256 0.0000016 0.00000020 158.40 6335.8 313701 0.0
9 512 0.0000032 0.00000021 162.53 7313.8 160943 0.1
10 1024 0.0000067 0.00000023 152.53 7626.5 75521 0.1
11 2048 0.0000136 0.00000025 150.42 8273.3 37239 0.2
12 4096 0.0000316 0.00000027 129.75 7784.8 16060 0.3
13 8192 0.0000720 0.00000026 113.75 7393.8 7040 0.5
14 16384 0.0001620 0.00000028 101.11 7078.0 3129 0.9
15 32768 0.0003227 0.00000030 101.53 7615.1 1571 1.7
16 65536 0.0010020 0.00000030 65.41 5232.5 506 4.1
17 131072 0.0021575 0.00000032 60.75 5164.0 235 0.0
18 262144 0.0053937 0.00000032 48.60 4374.2 94 3.6
19 524288 0.0190668 0.00000034 27.50 2612.2 27 6.8
20 1048576 0.0468001 0.00000035 22.41 2240.5 11 2.4
21 2097152 0.0936012 0.00000036 22.41 2352.5 6 31.6
22 4194304 0.1949997 0.00000037 21.51 2366.0 3 9.8
23 8388608 0.4212036 0.00000038 19.92 2290.3 2 112.9
#######################################################################
Test data for all transforms is gaussian random noise of zero mean and
standard deviation 1. Tabulated values of "rms" are the
root-mean-square differences between the original data and the
back-transfmred data.
File nfft.dat contains all numbers between 2^3 and 2^23 that have
no factor greater than 7, followed by their factors. These numbers
are good choices for FFT lengths.