Several tweaks to chkfft.f90. Add descriptive file chkfft.txt.

git-svn-id: svn+ssh://svn.code.sf.net/p/wsjt/wsjt/branches/wsjtx@4836 ab8295b8-cf94-4d9e-aec4-7959e3be5d79
This commit is contained in:
Joe Taylor 2014-12-18 20:34:06 +00:00
parent 22e15084e1
commit 1889b24c78
2 changed files with 135 additions and 15 deletions

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@ -16,16 +16,18 @@ program chkfft
nargs=iargc() nargs=iargc()
if(nargs.ne.5) then if(nargs.ne.5) then
print*,'Usage: chkfft <nfft | infile> nr nw nc np' print*,'Usage: chkfft <nfft | infile> nr nw nc np'
print*,' nr: 0/1 for read wisdom' print*,' nfft: length of FFT'
print*,' nw: 0/1 for write wisdom' print*,' nfft=0: do lengths 2^n, n=2^4 to 2^23'
print*,' nc: 0/1 for real/complex' print*,' infile: name of file with nfft values, one per line'
print*,' np: patience, 0-4' print*,' nr: 0/1 to not read (or read) wisdom'
print*,' negative nfft: powers of 2 up to 2^(-nfft)' print*,' nw: 0/1 to not write (or write) wisdom'
print*,' nc: 0/1 for real or complex data'
print*,' np: 0-4 patience for finding best algorithm'
go to 999 go to 999
endif endif
list=.false. list=.false.
nfft=0 nfft=-1
call getarg(1,infile) call getarg(1,infile)
open(10,file=infile,status='old',err=1) open(10,file=infile,status='old',err=1)
list=.true. !A valid file name was provided list=.true. !A valid file name was provided
@ -46,12 +48,15 @@ program chkfft
1002 format(/'nfft: ',i10,' nr:',i2,' nw',i2,' nc:',i2,' np:',i2/) 1002 format(/'nfft: ',i10,' nr:',i2,' nw',i2,' nc:',i2,' np:',i2/)
open(12,file='chkfft.out',status='unknown') open(12,file='chkfft.out',status='unknown')
open(13,file='fftw_wisdom.dat',status='unknown') open(13,file='fftwf_wisdom.dat',status='unknown')
if(nr.ne.0) then if(nr.ne.0) then
call import_wisdom_from_file(isuccess,13) call import_wisdom_from_file(isuccess,13)
if(isuccess.ne.0) write(*,1010) if(isuccess.eq.0) then
1010 format('Imported FFTW wisdom') write(*,1010)
1010 format('Failed to import FFTW wisdom.')
go to 999
endif
endif endif
idum=-1 !Set random seed idum=-1 !Set random seed
@ -72,7 +77,7 @@ program chkfft
' tplan'/61('-')) ' tplan'/61('-'))
else else
n1=4 n1=4
n2=min(-nfft,23) n2=23
write(*,1030) write(*,1030)
1030 format(' n N=2^n Time rms MHz MFlops iters', & 1030 format(' n N=2^n Time rms MHz MFlops iters', &
' tplan'/63('-')) ' tplan'/63('-'))
@ -118,7 +123,7 @@ program chkfft
if(tplan.lt.0) tplan=0. if(tplan.lt.0) tplan=0.
a(1:nfft)=a(1:nfft)/nfft a(1:nfft)=a(1:nfft)/nfft
! Compute RMS error ! Compute RMS difference between original array and back-transformed array.
sq=0. sq=0.
if(ncomplex.eq.1) then if(ncomplex.eq.1) then
do i=1,nfft do i=1,nfft
@ -133,7 +138,7 @@ program chkfft
freq=1.e-6*nfft/time freq=1.e-6*nfft/time
mflops=5.0/(1.e6*time/(nfft*log(float(nfft))/log(2.0))) mflops=5.0/(1.e6*time/(nfft*log(float(nfft))/log(2.0)))
if(n2.eq.999999) then if(n2.eq.1 .or. n2.eq.999999) then
write(*,1050) nfft,time,rms,freq,mflops,iter,tplan write(*,1050) nfft,time,rms,freq,mflops,iter,tplan
write(12,1050) nfft,time,rms,freq,mflops,iter,tplan write(12,1050) nfft,time,rms,freq,mflops,iter,tplan
1050 format(i8,f11.7,f12.8,f7.2,f8.1,i8,f6.1) 1050 format(i8,f11.7,f12.8,f7.2,f8.1,i8,f6.1)
@ -149,8 +154,8 @@ program chkfft
if(nw.eq.1) then if(nw.eq.1) then
rewind 13 rewind 13
call export_wisdom_to_file(13) call export_wisdom_to_file(13)
write(*,1070) ! write(*,1070)
1070 format('Exported FFTW wisdom') !1070 format(/'Exported FFTW wisdom')
endif endif
999 call four2a(0,-1,0,0,0) 999 call four2a(0,-1,0,0,0)

115
lib/chkfft.txt Normal file
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@ -0,0 +1,115 @@
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.