1. 13 Dec, 2016 2 commits
  2. 10 Dec, 2016 3 commits
  3. 03 Dec, 2016 1 commit
  4. 25 Nov, 2016 1 commit
  5. 24 Nov, 2016 1 commit
  6. 26 Oct, 2016 3 commits
  7. 18 Oct, 2016 1 commit
  8. 27 Sep, 2016 3 commits
  9. 18 Aug, 2016 3 commits
  10. 03 Aug, 2016 1 commit
  11. 22 Jun, 2016 1 commit
  12. 20 Jun, 2016 1 commit
  13. 17 Jun, 2016 2 commits
  14. 13 Jun, 2016 1 commit
    • Muhammad Faiz's avatar
      swresample: add exact_rational option · b8c6e5a6
      Muhammad Faiz authored
      give high quality resampling
      as good as with linear_interp=on
      as fast as without linear_interp=on
      tested visually with ffplay
      ffplay -f lavfi "aevalsrc='sin(10000*t*t)', aresample=osr=48000, showcqt=gamma=5"
      ffplay -f lavfi "aevalsrc='sin(10000*t*t)', aresample=osr=48000:linear_interp=on, showcqt=gamma=5"
      ffplay -f lavfi "aevalsrc='sin(10000*t*t)', aresample=osr=48000:exact_rational=on, showcqt=gamma=5"
      
      slightly speed improvement
      for fair comparison with -cpuflags 0
      audio.wav is ~ 1 hour 44100 stereo 16bit wav file
      ffmpeg -i audio.wav -af aresample=osr=48000 -f null -
              old         new
      real    13.498s     13.121s
      user    13.364s     12.987s
      sys      0.131s      0.129s
      
      linear_interp=on
              old         new
      real    23.035s     23.050s
      user    22.907s     22.917s
      sys      0.119s     0.125s
      
      exact_rational=on
      real    12.418s
      user    12.298s
      sys      0.114s
      
      possibility to decrease memory usage if soft compensation is ignored
      Signed-off-by: 's avatarMuhammad Faiz <mfcc64@gmail.com>
      b8c6e5a6
  15. 16 May, 2016 1 commit
  16. 15 May, 2016 2 commits
  17. 13 May, 2016 1 commit
  18. 22 Mar, 2016 1 commit
  19. 14 Feb, 2016 1 commit
  20. 31 Jan, 2016 1 commit
  21. 24 Dec, 2015 1 commit
  22. 04 Dec, 2015 1 commit
  23. 15 Nov, 2015 1 commit
  24. 11 Nov, 2015 1 commit
  25. 09 Nov, 2015 4 commits
    • Ganesh Ajjanagadde's avatar
      swresample/resample: speed up Blackman Nuttall filter · cf491a92
      Ganesh Ajjanagadde authored
      This may be a slightly surprising optimization, but is actually based on
      an understanding of how math libraries compute trigonometric functions.
      Explanation is given here so that future development uses libm more effectively
      across the codebase.
      
      All libm's essentially compute transcendental functions via some kind of
      polynomial approximation, be it Taylor-Maclaurin or Chebyshev.
      Correction terms are added via polynomial correction factors when needed
      to squeeze out the last bits of accuracy. Lookup tables are also
      inserted strategically.
      
      In the case of trigonometric functions, periodicity is exploited via
      first doing a range reduction to an interval around zero, and then using
      some polynomial approximation.
      
      This range reduction is the most natural way of doing things - else one
      would need polynomials for ranges in different periods which makes no
      sense whatsoever.
      
      To avoid the need for the range reduction, it is helpful to feed in
      arguments as close to the origin as possible for the trigonometric
      functions. In fact, this also makes sense from an accuracy point of view:
      IEEE floating point has far more resolution for small numbers than big ones.
      
      This patch does this for the Blackman-Nuttall filter, and yields a
      non-negligible speedup.
      
      Sample benchmark (x86-64, Haswell, GNU/Linux)
      test: fate-swr-resample-dblp-2626-44100
      old:
      18893514 decicycles in build_filter (loop 1000),     256 runs,      0 skips
      18599863 decicycles in build_filter (loop 1000),     512 runs,      0 skips
      18445574 decicycles in build_filter (loop 1000),    1000 runs,     24 skips
      
      new:
      16290697 decicycles in build_filter (loop 1000),     256 runs,      0 skips
      16267172 decicycles in build_filter (loop 1000),     512 runs,      0 skips
      16251105 decicycles in build_filter (loop 1000),    1000 runs,     24 skips
      Reviewed-by: 's avatarMichael Niedermayer <michael@niedermayer.cc>
      Signed-off-by: 's avatarGanesh Ajjanagadde <gajjanagadde@gmail.com>
      cf491a92
    • Ganesh Ajjanagadde's avatar
      swresample/resample: speed up upsampling by precomputing sines · b87ca4bf
      Ganesh Ajjanagadde authored
      When upsampling, factor is set to 1 and sines need to be evaluated only
      once for each phase, and the complexity should not depend on the number
      of filter taps. This does the desired precomputation, yielding
      significant speedups. Hard guarantees on the gain are not possible, but gains
      themselves are obvious and are illustrated below.
      
      Sample benchmark (x86-64, Haswell, GNU/Linux)
      test: fate-swr-resample-dblp-2626-44100
      old:
      29161085 decicycles in build_filter (loop 1000),     256 runs,      0 skips
      28821467 decicycles in build_filter (loop 1000),     512 runs,      0 skips
      28668201 decicycles in build_filter (loop 1000),    1000 runs,     24 skips
      
      new:
      14351936 decicycles in build_filter (loop 1000),     256 runs,      0 skips
      14306652 decicycles in build_filter (loop 1000),     512 runs,      0 skips
      14299923 decicycles in build_filter (loop 1000),    1000 runs,     24 skips
      
      Note that this does not statically allocate the sin lookup table. This
      may be done for the default 1024 phases, yielding a 512*8 = 4kB array
      which should be small enough.
      This should yield a small improvement. Nevertheless, this is separate from
      this patch, is more ambiguous due to the binary increase, and requires a
      lut to be generated offline.
      Reviewed-by: 's avatarMichael Niedermayer <michael@niedermayer.cc>
      Signed-off-by: 's avatarGanesh Ajjanagadde <gajjanagadde@gmail.com>
      b87ca4bf
    • Ganesh Ajjanagadde's avatar
      swresample/resample: improve bessel function accuracy and speed · a5202bc9
      Ganesh Ajjanagadde authored
      This improves accuracy for the bessel function at large arguments, and this in turn
      should improve the quality of the Kaiser window. It also improves the
      performance of the bessel function and hence build_filter by ~ 20%.
      Details are given below.
      
      Algorithm: taken from the Boost project, who have done a detailed
      investigation of the accuracy of their method, as compared with e.g the
      GNU Scientific Library (GSL):
      http://www.boost.org/doc/libs/1_52_0/libs/math/doc/sf_and_dist/html/math_toolkit/special/bessel/mbessel.html.
      Boost source code (also cited and licensed in the code):
      https://searchcode.com/codesearch/view/14918379/.
      
      Accuracy: sample values may be obtained as follows. i0 denotes the old bessel code,
      i0_boost the approach here, and i0_real an arbitrary precision result (truncated) from Wolfram Alpha:
      type "bessel i0(6.0)" to reproduce. These are evaluation points that occur for
      the default kaiser_beta = 9.
      
      Some illustrations:
      bessel(8.0)
      i0      (8.000000) = 427.564115721804739678191254
      i0_boost(8.000000) = 427.564115721804796521610115
      i0_real (8.000000) = 427.564115721804785177396791
      
      bessel(6.0)
      i0      (6.000000) = 67.234406976477956163762428
      i0_boost(6.000000) = 67.234406976477970374617144
      i0_real (6.000000) = 67.234406976477975326188025
      
      Reason for accuracy: Main accuracy benefits come at larger bessel arguments, where the
      Taylor-Maclaurin method is not that good: 23+ iterations
      (at large arguments, since the series is about 0) can cause
      significant floating point error accumulation.
      
      Benchmarks: Obtained on x86-64, Haswell, GNU/Linux via a loop calling
      build_filter 1000 times:
      test: fate-swr-resample-dblp-44100-2626
      
      new:
      995894468 decicycles in build_filter(loop 1000),     256 runs,      0 skips
      1029719302 decicycles in build_filter(loop 1000),     512 runs,      0 skips
      984101131 decicycles in build_filter(loop 1000),    1024 runs,      0 skips
      
      old:
      1250020763 decicycles in build_filter(loop 1000),     256 runs,      0 skips
      1246353282 decicycles in build_filter(loop 1000),     512 runs,      0 skips
      1220017565 decicycles in build_filter(loop 1000),    1024 runs,      0 skips
      
      A further ~ 5% may be squeezed by enabling -ftree-vectorize. However,
      this is a separate issue from this patch.
      Reviewed-by: 's avatarMichael Niedermayer <michael@niedermayer.cc>
      Signed-off-by: 's avatarGanesh Ajjanagadde <gajjanagadde@gmail.com>
      a5202bc9
    • Ganesh Ajjanagadde's avatar
      swresample: allow double precision beta value for the Kaiser window · 1bed09a3
      Ganesh Ajjanagadde authored
      Kaiser windows inherently don't require beta to be an integer. This was
      an arbitrary restriction. Moreover, soxr does not require it, and in
      fact often estimates beta to a non-integral value.
      
      Thus, this patch allows greater flexibility for swresample clients.
      Micro version is updated.
      Reviewed-by: 's avatarDerek Buitenhuis <derek.buitenhuis@gmail.com>
      Reviewed-by: 's avatarMichael Niedermayer <michael@niedermayer.cc>
      Signed-off-by: 's avatarGanesh Ajjanagadde <gajjanagadde@gmail.com>
      1bed09a3
  26. 06 Nov, 2015 1 commit
    • Ganesh Ajjanagadde's avatar
      swresample/resample: speed up build_filter for Blackman-Nuttall filter · c8780822
      Ganesh Ajjanagadde authored
      This uses the trigonometric double and triple angle formulae to avoid
      repeated (expensive) evaluation of libc's cos().
      
      Sample benchmark (x86-64, Haswell, GNU/Linux)
      test: fate-swr-resample-dblp-44100-2626
      old:
      1104466600 decicycles in build_filter(loop 1000),     256 runs,      0 skips
      1096765286 decicycles in build_filter(loop 1000),     512 runs,      0 skips
      1070479590 decicycles in build_filter(loop 1000),    1024 runs,      0 skips
      
      new:
      588861423 decicycles in build_filter(loop 1000),     256 runs,      0 skips
      591262754 decicycles in build_filter(loop 1000),     512 runs,      0 skips
      577355145 decicycles in build_filter(loop 1000),    1024 runs,      0 skips
      
      This results in small differences with the old expression:
      difference (worst case on [0, 2*M_PI]), argmax 0.008:
      max diff (relative): 0.000000000000157289807188
      blackman_old(0.008): 0.000363951585488813192382
      blackman_new(0.008): 0.000363951585488755946507
      
      These are judged to be insignificant for the performance gain. PSNR to
      reference file is unchanged up to second decimal point for instance.
      Reviewed-by: 's avatarMichael Niedermayer <michael@niedermayer.cc>
      Signed-off-by: 's avatarGanesh Ajjanagadde <gajjanagadde@gmail.com>
      c8780822