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FFmpeg/libavcodec/mdct15.c

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/*
* Copyright (c) 2013-2014 Mozilla Corporation
imdct15: replace the FFT with a faster PFA FFT algorithm This commit replaces the current inefficient non-power-of-two FFT with a much faster FFT based on the Prime Factor Algorithm. Although it is already much faster than the old algorithm without SIMD, the new algorithm makes use of the already very throughouly SIMD'd power of two FFT, which improves performance even more across all platforms which we have SIMD support for. Most of the work was done by Peter Barfuss, who passed the code to me to implement into the iMDCT and the current codebase. The code for a 5-point and 15-point FFT was derived from the previous implementation, although it was optimized and simplified, which will make its future SIMD easier. The 15-point FFT is currently using 6% of the current overall decoder overhead. The FFT can now easily be used as a forward transform by simply not multiplying the 5-point FFT's imaginary component by -1 (which comes from the fact that changing the complex exponential's angle by -1 also changes the output by that) and by multiplying the "theta" angle of the main exptab by -1. Hence the deliberately left multiplication by -1 at the end. FATE passes, and performance reports on other platforms/CPUs are welcome. Performance comparisons: iMDCT, PFA: 101127 decicycles in speed, 32765 runs, 3 skips iMDCT, Old: 211022 decicycles in speed, 32768 runs, 0 skips Standalone FFT, 300000 transforms of size 960: PFA Old FFT kiss_fft libfftw3f 3.659695s, 15.726912s, 13.300789s, 1.182222s Being only 3x slower than libfftw3f is a big achievement by itself. There appears to be something capping the performance in the iMDCT side of things, possibly during the pre-stage reindexing. However, it is certainly fast enough for now. Signed-off-by: Rostislav Pehlivanov <atomnuker@gmail.com>
2017-01-04 11:23:24 +02:00
* Copyright (c) 2017 Rostislav Pehlivanov <atomnuker@gmail.com>
*
* This file is part of FFmpeg.
*
* FFmpeg is free software; you can redistribute it and/or
* modify it under the terms of the GNU Lesser General Public
* License as published by the Free Software Foundation; either
* version 2.1 of the License, or (at your option) any later version.
*
* FFmpeg is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
* Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public
* License along with FFmpeg; if not, write to the Free Software
* Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
*/
/**
* @file
* Celt non-power of 2 iMDCT
*/
#include <float.h>
#include <math.h>
#include <stddef.h>
#include <stdint.h>
#include "config.h"
#include "libavutil/attributes.h"
#include "libavutil/error.h"
#include "mdct15.h"
#define FFT_FLOAT 1
#include "fft-internal.h"
#define CMUL3(c, a, b) CMUL((c).re, (c).im, (a).re, (a).im, (b).re, (b).im)
av_cold void ff_mdct15_uninit(MDCT15Context **ps)
{
MDCT15Context *s = *ps;
if (!s)
return;
imdct15: replace the FFT with a faster PFA FFT algorithm This commit replaces the current inefficient non-power-of-two FFT with a much faster FFT based on the Prime Factor Algorithm. Although it is already much faster than the old algorithm without SIMD, the new algorithm makes use of the already very throughouly SIMD'd power of two FFT, which improves performance even more across all platforms which we have SIMD support for. Most of the work was done by Peter Barfuss, who passed the code to me to implement into the iMDCT and the current codebase. The code for a 5-point and 15-point FFT was derived from the previous implementation, although it was optimized and simplified, which will make its future SIMD easier. The 15-point FFT is currently using 6% of the current overall decoder overhead. The FFT can now easily be used as a forward transform by simply not multiplying the 5-point FFT's imaginary component by -1 (which comes from the fact that changing the complex exponential's angle by -1 also changes the output by that) and by multiplying the "theta" angle of the main exptab by -1. Hence the deliberately left multiplication by -1 at the end. FATE passes, and performance reports on other platforms/CPUs are welcome. Performance comparisons: iMDCT, PFA: 101127 decicycles in speed, 32765 runs, 3 skips iMDCT, Old: 211022 decicycles in speed, 32768 runs, 0 skips Standalone FFT, 300000 transforms of size 960: PFA Old FFT kiss_fft libfftw3f 3.659695s, 15.726912s, 13.300789s, 1.182222s Being only 3x slower than libfftw3f is a big achievement by itself. There appears to be something capping the performance in the iMDCT side of things, possibly during the pre-stage reindexing. However, it is certainly fast enough for now. Signed-off-by: Rostislav Pehlivanov <atomnuker@gmail.com>
2017-01-04 11:23:24 +02:00
ff_fft_end(&s->ptwo_fft);
imdct15: replace the FFT with a faster PFA FFT algorithm This commit replaces the current inefficient non-power-of-two FFT with a much faster FFT based on the Prime Factor Algorithm. Although it is already much faster than the old algorithm without SIMD, the new algorithm makes use of the already very throughouly SIMD'd power of two FFT, which improves performance even more across all platforms which we have SIMD support for. Most of the work was done by Peter Barfuss, who passed the code to me to implement into the iMDCT and the current codebase. The code for a 5-point and 15-point FFT was derived from the previous implementation, although it was optimized and simplified, which will make its future SIMD easier. The 15-point FFT is currently using 6% of the current overall decoder overhead. The FFT can now easily be used as a forward transform by simply not multiplying the 5-point FFT's imaginary component by -1 (which comes from the fact that changing the complex exponential's angle by -1 also changes the output by that) and by multiplying the "theta" angle of the main exptab by -1. Hence the deliberately left multiplication by -1 at the end. FATE passes, and performance reports on other platforms/CPUs are welcome. Performance comparisons: iMDCT, PFA: 101127 decicycles in speed, 32765 runs, 3 skips iMDCT, Old: 211022 decicycles in speed, 32768 runs, 0 skips Standalone FFT, 300000 transforms of size 960: PFA Old FFT kiss_fft libfftw3f 3.659695s, 15.726912s, 13.300789s, 1.182222s Being only 3x slower than libfftw3f is a big achievement by itself. There appears to be something capping the performance in the iMDCT side of things, possibly during the pre-stage reindexing. However, it is certainly fast enough for now. Signed-off-by: Rostislav Pehlivanov <atomnuker@gmail.com>
2017-01-04 11:23:24 +02:00
av_freep(&s->pfa_prereindex);
av_freep(&s->pfa_postreindex);
av_freep(&s->twiddle_exptab);
av_freep(&s->tmp);
av_freep(ps);
}
static inline int init_pfa_reindex_tabs(MDCT15Context *s)
imdct15: replace the FFT with a faster PFA FFT algorithm This commit replaces the current inefficient non-power-of-two FFT with a much faster FFT based on the Prime Factor Algorithm. Although it is already much faster than the old algorithm without SIMD, the new algorithm makes use of the already very throughouly SIMD'd power of two FFT, which improves performance even more across all platforms which we have SIMD support for. Most of the work was done by Peter Barfuss, who passed the code to me to implement into the iMDCT and the current codebase. The code for a 5-point and 15-point FFT was derived from the previous implementation, although it was optimized and simplified, which will make its future SIMD easier. The 15-point FFT is currently using 6% of the current overall decoder overhead. The FFT can now easily be used as a forward transform by simply not multiplying the 5-point FFT's imaginary component by -1 (which comes from the fact that changing the complex exponential's angle by -1 also changes the output by that) and by multiplying the "theta" angle of the main exptab by -1. Hence the deliberately left multiplication by -1 at the end. FATE passes, and performance reports on other platforms/CPUs are welcome. Performance comparisons: iMDCT, PFA: 101127 decicycles in speed, 32765 runs, 3 skips iMDCT, Old: 211022 decicycles in speed, 32768 runs, 0 skips Standalone FFT, 300000 transforms of size 960: PFA Old FFT kiss_fft libfftw3f 3.659695s, 15.726912s, 13.300789s, 1.182222s Being only 3x slower than libfftw3f is a big achievement by itself. There appears to be something capping the performance in the iMDCT side of things, possibly during the pre-stage reindexing. However, it is certainly fast enough for now. Signed-off-by: Rostislav Pehlivanov <atomnuker@gmail.com>
2017-01-04 11:23:24 +02:00
{
int i, j;
const int b_ptwo = s->ptwo_fft.nbits; /* Bits for the power of two FFTs */
const int l_ptwo = 1 << b_ptwo; /* Total length for the power of two FFTs */
const int inv_1 = l_ptwo << ((4 - b_ptwo) & 3); /* (2^b_ptwo)^-1 mod 15 */
const int inv_2 = 0xeeeeeeef & ((1U << b_ptwo) - 1); /* 15^-1 mod 2^b_ptwo */
s->pfa_prereindex = av_malloc_array(15 * l_ptwo, sizeof(*s->pfa_prereindex));
imdct15: replace the FFT with a faster PFA FFT algorithm This commit replaces the current inefficient non-power-of-two FFT with a much faster FFT based on the Prime Factor Algorithm. Although it is already much faster than the old algorithm without SIMD, the new algorithm makes use of the already very throughouly SIMD'd power of two FFT, which improves performance even more across all platforms which we have SIMD support for. Most of the work was done by Peter Barfuss, who passed the code to me to implement into the iMDCT and the current codebase. The code for a 5-point and 15-point FFT was derived from the previous implementation, although it was optimized and simplified, which will make its future SIMD easier. The 15-point FFT is currently using 6% of the current overall decoder overhead. The FFT can now easily be used as a forward transform by simply not multiplying the 5-point FFT's imaginary component by -1 (which comes from the fact that changing the complex exponential's angle by -1 also changes the output by that) and by multiplying the "theta" angle of the main exptab by -1. Hence the deliberately left multiplication by -1 at the end. FATE passes, and performance reports on other platforms/CPUs are welcome. Performance comparisons: iMDCT, PFA: 101127 decicycles in speed, 32765 runs, 3 skips iMDCT, Old: 211022 decicycles in speed, 32768 runs, 0 skips Standalone FFT, 300000 transforms of size 960: PFA Old FFT kiss_fft libfftw3f 3.659695s, 15.726912s, 13.300789s, 1.182222s Being only 3x slower than libfftw3f is a big achievement by itself. There appears to be something capping the performance in the iMDCT side of things, possibly during the pre-stage reindexing. However, it is certainly fast enough for now. Signed-off-by: Rostislav Pehlivanov <atomnuker@gmail.com>
2017-01-04 11:23:24 +02:00
if (!s->pfa_prereindex)
return 1;
s->pfa_postreindex = av_malloc_array(15 * l_ptwo, sizeof(*s->pfa_postreindex));
imdct15: replace the FFT with a faster PFA FFT algorithm This commit replaces the current inefficient non-power-of-two FFT with a much faster FFT based on the Prime Factor Algorithm. Although it is already much faster than the old algorithm without SIMD, the new algorithm makes use of the already very throughouly SIMD'd power of two FFT, which improves performance even more across all platforms which we have SIMD support for. Most of the work was done by Peter Barfuss, who passed the code to me to implement into the iMDCT and the current codebase. The code for a 5-point and 15-point FFT was derived from the previous implementation, although it was optimized and simplified, which will make its future SIMD easier. The 15-point FFT is currently using 6% of the current overall decoder overhead. The FFT can now easily be used as a forward transform by simply not multiplying the 5-point FFT's imaginary component by -1 (which comes from the fact that changing the complex exponential's angle by -1 also changes the output by that) and by multiplying the "theta" angle of the main exptab by -1. Hence the deliberately left multiplication by -1 at the end. FATE passes, and performance reports on other platforms/CPUs are welcome. Performance comparisons: iMDCT, PFA: 101127 decicycles in speed, 32765 runs, 3 skips iMDCT, Old: 211022 decicycles in speed, 32768 runs, 0 skips Standalone FFT, 300000 transforms of size 960: PFA Old FFT kiss_fft libfftw3f 3.659695s, 15.726912s, 13.300789s, 1.182222s Being only 3x slower than libfftw3f is a big achievement by itself. There appears to be something capping the performance in the iMDCT side of things, possibly during the pre-stage reindexing. However, it is certainly fast enough for now. Signed-off-by: Rostislav Pehlivanov <atomnuker@gmail.com>
2017-01-04 11:23:24 +02:00
if (!s->pfa_postreindex)
return 1;
/* Pre/Post-reindex */
for (i = 0; i < l_ptwo; i++) {
for (j = 0; j < 15; j++) {
const int q_pre = ((l_ptwo * j)/15 + i) >> b_ptwo;
const int q_post = (((j*inv_1)/15) + (i*inv_2)) >> b_ptwo;
const int k_pre = 15*i + (j - q_pre*15)*(1 << b_ptwo);
imdct15: replace the FFT with a faster PFA FFT algorithm This commit replaces the current inefficient non-power-of-two FFT with a much faster FFT based on the Prime Factor Algorithm. Although it is already much faster than the old algorithm without SIMD, the new algorithm makes use of the already very throughouly SIMD'd power of two FFT, which improves performance even more across all platforms which we have SIMD support for. Most of the work was done by Peter Barfuss, who passed the code to me to implement into the iMDCT and the current codebase. The code for a 5-point and 15-point FFT was derived from the previous implementation, although it was optimized and simplified, which will make its future SIMD easier. The 15-point FFT is currently using 6% of the current overall decoder overhead. The FFT can now easily be used as a forward transform by simply not multiplying the 5-point FFT's imaginary component by -1 (which comes from the fact that changing the complex exponential's angle by -1 also changes the output by that) and by multiplying the "theta" angle of the main exptab by -1. Hence the deliberately left multiplication by -1 at the end. FATE passes, and performance reports on other platforms/CPUs are welcome. Performance comparisons: iMDCT, PFA: 101127 decicycles in speed, 32765 runs, 3 skips iMDCT, Old: 211022 decicycles in speed, 32768 runs, 0 skips Standalone FFT, 300000 transforms of size 960: PFA Old FFT kiss_fft libfftw3f 3.659695s, 15.726912s, 13.300789s, 1.182222s Being only 3x slower than libfftw3f is a big achievement by itself. There appears to be something capping the performance in the iMDCT side of things, possibly during the pre-stage reindexing. However, it is certainly fast enough for now. Signed-off-by: Rostislav Pehlivanov <atomnuker@gmail.com>
2017-01-04 11:23:24 +02:00
const int k_post = i*inv_2*15 + j*inv_1 - 15*q_post*l_ptwo;
s->pfa_prereindex[i*15 + j] = k_pre << 1;
imdct15: replace the FFT with a faster PFA FFT algorithm This commit replaces the current inefficient non-power-of-two FFT with a much faster FFT based on the Prime Factor Algorithm. Although it is already much faster than the old algorithm without SIMD, the new algorithm makes use of the already very throughouly SIMD'd power of two FFT, which improves performance even more across all platforms which we have SIMD support for. Most of the work was done by Peter Barfuss, who passed the code to me to implement into the iMDCT and the current codebase. The code for a 5-point and 15-point FFT was derived from the previous implementation, although it was optimized and simplified, which will make its future SIMD easier. The 15-point FFT is currently using 6% of the current overall decoder overhead. The FFT can now easily be used as a forward transform by simply not multiplying the 5-point FFT's imaginary component by -1 (which comes from the fact that changing the complex exponential's angle by -1 also changes the output by that) and by multiplying the "theta" angle of the main exptab by -1. Hence the deliberately left multiplication by -1 at the end. FATE passes, and performance reports on other platforms/CPUs are welcome. Performance comparisons: iMDCT, PFA: 101127 decicycles in speed, 32765 runs, 3 skips iMDCT, Old: 211022 decicycles in speed, 32768 runs, 0 skips Standalone FFT, 300000 transforms of size 960: PFA Old FFT kiss_fft libfftw3f 3.659695s, 15.726912s, 13.300789s, 1.182222s Being only 3x slower than libfftw3f is a big achievement by itself. There appears to be something capping the performance in the iMDCT side of things, possibly during the pre-stage reindexing. However, it is certainly fast enough for now. Signed-off-by: Rostislav Pehlivanov <atomnuker@gmail.com>
2017-01-04 11:23:24 +02:00
s->pfa_postreindex[k_post] = l_ptwo*j + i;
}
}
return 0;
}
/* Stride is hardcoded to 3 */
static inline void fft5(FFTComplex *out, FFTComplex *in, FFTComplex exptab[2])
{
imdct15: replace the FFT with a faster PFA FFT algorithm This commit replaces the current inefficient non-power-of-two FFT with a much faster FFT based on the Prime Factor Algorithm. Although it is already much faster than the old algorithm without SIMD, the new algorithm makes use of the already very throughouly SIMD'd power of two FFT, which improves performance even more across all platforms which we have SIMD support for. Most of the work was done by Peter Barfuss, who passed the code to me to implement into the iMDCT and the current codebase. The code for a 5-point and 15-point FFT was derived from the previous implementation, although it was optimized and simplified, which will make its future SIMD easier. The 15-point FFT is currently using 6% of the current overall decoder overhead. The FFT can now easily be used as a forward transform by simply not multiplying the 5-point FFT's imaginary component by -1 (which comes from the fact that changing the complex exponential's angle by -1 also changes the output by that) and by multiplying the "theta" angle of the main exptab by -1. Hence the deliberately left multiplication by -1 at the end. FATE passes, and performance reports on other platforms/CPUs are welcome. Performance comparisons: iMDCT, PFA: 101127 decicycles in speed, 32765 runs, 3 skips iMDCT, Old: 211022 decicycles in speed, 32768 runs, 0 skips Standalone FFT, 300000 transforms of size 960: PFA Old FFT kiss_fft libfftw3f 3.659695s, 15.726912s, 13.300789s, 1.182222s Being only 3x slower than libfftw3f is a big achievement by itself. There appears to be something capping the performance in the iMDCT side of things, possibly during the pre-stage reindexing. However, it is certainly fast enough for now. Signed-off-by: Rostislav Pehlivanov <atomnuker@gmail.com>
2017-01-04 11:23:24 +02:00
FFTComplex z0[4], t[6];
t[0].re = in[3].re + in[12].re;
t[0].im = in[3].im + in[12].im;
t[1].im = in[3].re - in[12].re;
t[1].re = in[3].im - in[12].im;
t[2].re = in[6].re + in[ 9].re;
t[2].im = in[6].im + in[ 9].im;
t[3].im = in[6].re - in[ 9].re;
t[3].re = in[6].im - in[ 9].im;
out[0].re = in[0].re + in[3].re + in[6].re + in[9].re + in[12].re;
out[0].im = in[0].im + in[3].im + in[6].im + in[9].im + in[12].im;
t[4].re = exptab[0].re * t[2].re - exptab[1].re * t[0].re;
t[4].im = exptab[0].re * t[2].im - exptab[1].re * t[0].im;
t[0].re = exptab[0].re * t[0].re - exptab[1].re * t[2].re;
t[0].im = exptab[0].re * t[0].im - exptab[1].re * t[2].im;
t[5].re = exptab[0].im * t[3].re - exptab[1].im * t[1].re;
t[5].im = exptab[0].im * t[3].im - exptab[1].im * t[1].im;
t[1].re = exptab[0].im * t[1].re + exptab[1].im * t[3].re;
t[1].im = exptab[0].im * t[1].im + exptab[1].im * t[3].im;
z0[0].re = t[0].re - t[1].re;
z0[0].im = t[0].im - t[1].im;
z0[1].re = t[4].re + t[5].re;
z0[1].im = t[4].im + t[5].im;
z0[2].re = t[4].re - t[5].re;
z0[2].im = t[4].im - t[5].im;
z0[3].re = t[0].re + t[1].re;
z0[3].im = t[0].im + t[1].im;
out[1].re = in[0].re + z0[3].re;
out[1].im = in[0].im + z0[0].im;
out[2].re = in[0].re + z0[2].re;
out[2].im = in[0].im + z0[1].im;
out[3].re = in[0].re + z0[1].re;
out[3].im = in[0].im + z0[2].im;
out[4].re = in[0].re + z0[0].re;
out[4].im = in[0].im + z0[3].im;
}
static void fft15_c(FFTComplex *out, FFTComplex *in, FFTComplex *exptab, ptrdiff_t stride)
{
int k;
imdct15: replace the FFT with a faster PFA FFT algorithm This commit replaces the current inefficient non-power-of-two FFT with a much faster FFT based on the Prime Factor Algorithm. Although it is already much faster than the old algorithm without SIMD, the new algorithm makes use of the already very throughouly SIMD'd power of two FFT, which improves performance even more across all platforms which we have SIMD support for. Most of the work was done by Peter Barfuss, who passed the code to me to implement into the iMDCT and the current codebase. The code for a 5-point and 15-point FFT was derived from the previous implementation, although it was optimized and simplified, which will make its future SIMD easier. The 15-point FFT is currently using 6% of the current overall decoder overhead. The FFT can now easily be used as a forward transform by simply not multiplying the 5-point FFT's imaginary component by -1 (which comes from the fact that changing the complex exponential's angle by -1 also changes the output by that) and by multiplying the "theta" angle of the main exptab by -1. Hence the deliberately left multiplication by -1 at the end. FATE passes, and performance reports on other platforms/CPUs are welcome. Performance comparisons: iMDCT, PFA: 101127 decicycles in speed, 32765 runs, 3 skips iMDCT, Old: 211022 decicycles in speed, 32768 runs, 0 skips Standalone FFT, 300000 transforms of size 960: PFA Old FFT kiss_fft libfftw3f 3.659695s, 15.726912s, 13.300789s, 1.182222s Being only 3x slower than libfftw3f is a big achievement by itself. There appears to be something capping the performance in the iMDCT side of things, possibly during the pre-stage reindexing. However, it is certainly fast enough for now. Signed-off-by: Rostislav Pehlivanov <atomnuker@gmail.com>
2017-01-04 11:23:24 +02:00
FFTComplex tmp1[5], tmp2[5], tmp3[5];
fft5(tmp1, in + 0, exptab + 19);
fft5(tmp2, in + 1, exptab + 19);
fft5(tmp3, in + 2, exptab + 19);
for (k = 0; k < 5; k++) {
imdct15: replace the FFT with a faster PFA FFT algorithm This commit replaces the current inefficient non-power-of-two FFT with a much faster FFT based on the Prime Factor Algorithm. Although it is already much faster than the old algorithm without SIMD, the new algorithm makes use of the already very throughouly SIMD'd power of two FFT, which improves performance even more across all platforms which we have SIMD support for. Most of the work was done by Peter Barfuss, who passed the code to me to implement into the iMDCT and the current codebase. The code for a 5-point and 15-point FFT was derived from the previous implementation, although it was optimized and simplified, which will make its future SIMD easier. The 15-point FFT is currently using 6% of the current overall decoder overhead. The FFT can now easily be used as a forward transform by simply not multiplying the 5-point FFT's imaginary component by -1 (which comes from the fact that changing the complex exponential's angle by -1 also changes the output by that) and by multiplying the "theta" angle of the main exptab by -1. Hence the deliberately left multiplication by -1 at the end. FATE passes, and performance reports on other platforms/CPUs are welcome. Performance comparisons: iMDCT, PFA: 101127 decicycles in speed, 32765 runs, 3 skips iMDCT, Old: 211022 decicycles in speed, 32768 runs, 0 skips Standalone FFT, 300000 transforms of size 960: PFA Old FFT kiss_fft libfftw3f 3.659695s, 15.726912s, 13.300789s, 1.182222s Being only 3x slower than libfftw3f is a big achievement by itself. There appears to be something capping the performance in the iMDCT side of things, possibly during the pre-stage reindexing. However, it is certainly fast enough for now. Signed-off-by: Rostislav Pehlivanov <atomnuker@gmail.com>
2017-01-04 11:23:24 +02:00
FFTComplex t[2];
CMUL3(t[0], tmp2[k], exptab[k]);
CMUL3(t[1], tmp3[k], exptab[2 * k]);
imdct15: replace the FFT with a faster PFA FFT algorithm This commit replaces the current inefficient non-power-of-two FFT with a much faster FFT based on the Prime Factor Algorithm. Although it is already much faster than the old algorithm without SIMD, the new algorithm makes use of the already very throughouly SIMD'd power of two FFT, which improves performance even more across all platforms which we have SIMD support for. Most of the work was done by Peter Barfuss, who passed the code to me to implement into the iMDCT and the current codebase. The code for a 5-point and 15-point FFT was derived from the previous implementation, although it was optimized and simplified, which will make its future SIMD easier. The 15-point FFT is currently using 6% of the current overall decoder overhead. The FFT can now easily be used as a forward transform by simply not multiplying the 5-point FFT's imaginary component by -1 (which comes from the fact that changing the complex exponential's angle by -1 also changes the output by that) and by multiplying the "theta" angle of the main exptab by -1. Hence the deliberately left multiplication by -1 at the end. FATE passes, and performance reports on other platforms/CPUs are welcome. Performance comparisons: iMDCT, PFA: 101127 decicycles in speed, 32765 runs, 3 skips iMDCT, Old: 211022 decicycles in speed, 32768 runs, 0 skips Standalone FFT, 300000 transforms of size 960: PFA Old FFT kiss_fft libfftw3f 3.659695s, 15.726912s, 13.300789s, 1.182222s Being only 3x slower than libfftw3f is a big achievement by itself. There appears to be something capping the performance in the iMDCT side of things, possibly during the pre-stage reindexing. However, it is certainly fast enough for now. Signed-off-by: Rostislav Pehlivanov <atomnuker@gmail.com>
2017-01-04 11:23:24 +02:00
out[stride*k].re = tmp1[k].re + t[0].re + t[1].re;
out[stride*k].im = tmp1[k].im + t[0].im + t[1].im;
CMUL3(t[0], tmp2[k], exptab[k + 5]);
CMUL3(t[1], tmp3[k], exptab[2 * (k + 5)]);
imdct15: replace the FFT with a faster PFA FFT algorithm This commit replaces the current inefficient non-power-of-two FFT with a much faster FFT based on the Prime Factor Algorithm. Although it is already much faster than the old algorithm without SIMD, the new algorithm makes use of the already very throughouly SIMD'd power of two FFT, which improves performance even more across all platforms which we have SIMD support for. Most of the work was done by Peter Barfuss, who passed the code to me to implement into the iMDCT and the current codebase. The code for a 5-point and 15-point FFT was derived from the previous implementation, although it was optimized and simplified, which will make its future SIMD easier. The 15-point FFT is currently using 6% of the current overall decoder overhead. The FFT can now easily be used as a forward transform by simply not multiplying the 5-point FFT's imaginary component by -1 (which comes from the fact that changing the complex exponential's angle by -1 also changes the output by that) and by multiplying the "theta" angle of the main exptab by -1. Hence the deliberately left multiplication by -1 at the end. FATE passes, and performance reports on other platforms/CPUs are welcome. Performance comparisons: iMDCT, PFA: 101127 decicycles in speed, 32765 runs, 3 skips iMDCT, Old: 211022 decicycles in speed, 32768 runs, 0 skips Standalone FFT, 300000 transforms of size 960: PFA Old FFT kiss_fft libfftw3f 3.659695s, 15.726912s, 13.300789s, 1.182222s Being only 3x slower than libfftw3f is a big achievement by itself. There appears to be something capping the performance in the iMDCT side of things, possibly during the pre-stage reindexing. However, it is certainly fast enough for now. Signed-off-by: Rostislav Pehlivanov <atomnuker@gmail.com>
2017-01-04 11:23:24 +02:00
out[stride*(k + 5)].re = tmp1[k].re + t[0].re + t[1].re;
out[stride*(k + 5)].im = tmp1[k].im + t[0].im + t[1].im;
CMUL3(t[0], tmp2[k], exptab[k + 10]);
CMUL3(t[1], tmp3[k], exptab[2 * k + 5]);
imdct15: replace the FFT with a faster PFA FFT algorithm This commit replaces the current inefficient non-power-of-two FFT with a much faster FFT based on the Prime Factor Algorithm. Although it is already much faster than the old algorithm without SIMD, the new algorithm makes use of the already very throughouly SIMD'd power of two FFT, which improves performance even more across all platforms which we have SIMD support for. Most of the work was done by Peter Barfuss, who passed the code to me to implement into the iMDCT and the current codebase. The code for a 5-point and 15-point FFT was derived from the previous implementation, although it was optimized and simplified, which will make its future SIMD easier. The 15-point FFT is currently using 6% of the current overall decoder overhead. The FFT can now easily be used as a forward transform by simply not multiplying the 5-point FFT's imaginary component by -1 (which comes from the fact that changing the complex exponential's angle by -1 also changes the output by that) and by multiplying the "theta" angle of the main exptab by -1. Hence the deliberately left multiplication by -1 at the end. FATE passes, and performance reports on other platforms/CPUs are welcome. Performance comparisons: iMDCT, PFA: 101127 decicycles in speed, 32765 runs, 3 skips iMDCT, Old: 211022 decicycles in speed, 32768 runs, 0 skips Standalone FFT, 300000 transforms of size 960: PFA Old FFT kiss_fft libfftw3f 3.659695s, 15.726912s, 13.300789s, 1.182222s Being only 3x slower than libfftw3f is a big achievement by itself. There appears to be something capping the performance in the iMDCT side of things, possibly during the pre-stage reindexing. However, it is certainly fast enough for now. Signed-off-by: Rostislav Pehlivanov <atomnuker@gmail.com>
2017-01-04 11:23:24 +02:00
out[stride*(k + 10)].re = tmp1[k].re + t[0].re + t[1].re;
out[stride*(k + 10)].im = tmp1[k].im + t[0].im + t[1].im;
}
}
static void mdct15(MDCT15Context *s, float *dst, const float *src, ptrdiff_t stride)
{
int i, j;
const int len4 = s->len4, len3 = len4 * 3, len8 = len4 >> 1;
const int l_ptwo = 1 << s->ptwo_fft.nbits;
FFTComplex fft15in[15];
/* Folding and pre-reindexing */
for (i = 0; i < l_ptwo; i++) {
for (j = 0; j < 15; j++) {
const int k = s->pfa_prereindex[i*15 + j];
FFTComplex tmp, exp = s->twiddle_exptab[k >> 1];
if (k < len4) {
tmp.re = -src[ len4 + k] + src[1*len4 - 1 - k];
tmp.im = -src[ len3 + k] - src[1*len3 - 1 - k];
} else {
tmp.re = -src[ len4 + k] - src[5*len4 - 1 - k];
tmp.im = src[-len4 + k] - src[1*len3 - 1 - k];
}
CMUL(fft15in[j].im, fft15in[j].re, tmp.re, tmp.im, exp.re, exp.im);
}
s->fft15(s->tmp + s->ptwo_fft.revtab[i], fft15in, s->exptab, l_ptwo);
}
/* Then a 15xN FFT (where N is a power of two) */
for (i = 0; i < 15; i++)
s->ptwo_fft.fft_calc(&s->ptwo_fft, s->tmp + l_ptwo*i);
/* Reindex again, apply twiddles and output */
for (i = 0; i < len8; i++) {
const int i0 = len8 + i, i1 = len8 - i - 1;
const int s0 = s->pfa_postreindex[i0], s1 = s->pfa_postreindex[i1];
CMUL(dst[2*i1*stride + stride], dst[2*i0*stride], s->tmp[s0].re, s->tmp[s0].im,
s->twiddle_exptab[i0].im, s->twiddle_exptab[i0].re);
CMUL(dst[2*i0*stride + stride], dst[2*i1*stride], s->tmp[s1].re, s->tmp[s1].im,
s->twiddle_exptab[i1].im, s->twiddle_exptab[i1].re);
}
}
static void imdct15_half(MDCT15Context *s, float *dst, const float *src,
ptrdiff_t stride)
{
imdct15: replace the FFT with a faster PFA FFT algorithm This commit replaces the current inefficient non-power-of-two FFT with a much faster FFT based on the Prime Factor Algorithm. Although it is already much faster than the old algorithm without SIMD, the new algorithm makes use of the already very throughouly SIMD'd power of two FFT, which improves performance even more across all platforms which we have SIMD support for. Most of the work was done by Peter Barfuss, who passed the code to me to implement into the iMDCT and the current codebase. The code for a 5-point and 15-point FFT was derived from the previous implementation, although it was optimized and simplified, which will make its future SIMD easier. The 15-point FFT is currently using 6% of the current overall decoder overhead. The FFT can now easily be used as a forward transform by simply not multiplying the 5-point FFT's imaginary component by -1 (which comes from the fact that changing the complex exponential's angle by -1 also changes the output by that) and by multiplying the "theta" angle of the main exptab by -1. Hence the deliberately left multiplication by -1 at the end. FATE passes, and performance reports on other platforms/CPUs are welcome. Performance comparisons: iMDCT, PFA: 101127 decicycles in speed, 32765 runs, 3 skips iMDCT, Old: 211022 decicycles in speed, 32768 runs, 0 skips Standalone FFT, 300000 transforms of size 960: PFA Old FFT kiss_fft libfftw3f 3.659695s, 15.726912s, 13.300789s, 1.182222s Being only 3x slower than libfftw3f is a big achievement by itself. There appears to be something capping the performance in the iMDCT side of things, possibly during the pre-stage reindexing. However, it is certainly fast enough for now. Signed-off-by: Rostislav Pehlivanov <atomnuker@gmail.com>
2017-01-04 11:23:24 +02:00
FFTComplex fft15in[15];
FFTComplex *z = (FFTComplex *)dst;
imdct15: replace the FFT with a faster PFA FFT algorithm This commit replaces the current inefficient non-power-of-two FFT with a much faster FFT based on the Prime Factor Algorithm. Although it is already much faster than the old algorithm without SIMD, the new algorithm makes use of the already very throughouly SIMD'd power of two FFT, which improves performance even more across all platforms which we have SIMD support for. Most of the work was done by Peter Barfuss, who passed the code to me to implement into the iMDCT and the current codebase. The code for a 5-point and 15-point FFT was derived from the previous implementation, although it was optimized and simplified, which will make its future SIMD easier. The 15-point FFT is currently using 6% of the current overall decoder overhead. The FFT can now easily be used as a forward transform by simply not multiplying the 5-point FFT's imaginary component by -1 (which comes from the fact that changing the complex exponential's angle by -1 also changes the output by that) and by multiplying the "theta" angle of the main exptab by -1. Hence the deliberately left multiplication by -1 at the end. FATE passes, and performance reports on other platforms/CPUs are welcome. Performance comparisons: iMDCT, PFA: 101127 decicycles in speed, 32765 runs, 3 skips iMDCT, Old: 211022 decicycles in speed, 32768 runs, 0 skips Standalone FFT, 300000 transforms of size 960: PFA Old FFT kiss_fft libfftw3f 3.659695s, 15.726912s, 13.300789s, 1.182222s Being only 3x slower than libfftw3f is a big achievement by itself. There appears to be something capping the performance in the iMDCT side of things, possibly during the pre-stage reindexing. However, it is certainly fast enough for now. Signed-off-by: Rostislav Pehlivanov <atomnuker@gmail.com>
2017-01-04 11:23:24 +02:00
int i, j, len8 = s->len4 >> 1, l_ptwo = 1 << s->ptwo_fft.nbits;
const float *in1 = src, *in2 = src + (s->len2 - 1) * stride;
/* Reindex input, putting it into a buffer and doing an Nx15 FFT */
for (i = 0; i < l_ptwo; i++) {
for (j = 0; j < 15; j++) {
const int k = s->pfa_prereindex[i*15 + j];
FFTComplex tmp = { in2[-k*stride], in1[k*stride] };
CMUL3(fft15in[j], tmp, s->twiddle_exptab[k >> 1]);
imdct15: replace the FFT with a faster PFA FFT algorithm This commit replaces the current inefficient non-power-of-two FFT with a much faster FFT based on the Prime Factor Algorithm. Although it is already much faster than the old algorithm without SIMD, the new algorithm makes use of the already very throughouly SIMD'd power of two FFT, which improves performance even more across all platforms which we have SIMD support for. Most of the work was done by Peter Barfuss, who passed the code to me to implement into the iMDCT and the current codebase. The code for a 5-point and 15-point FFT was derived from the previous implementation, although it was optimized and simplified, which will make its future SIMD easier. The 15-point FFT is currently using 6% of the current overall decoder overhead. The FFT can now easily be used as a forward transform by simply not multiplying the 5-point FFT's imaginary component by -1 (which comes from the fact that changing the complex exponential's angle by -1 also changes the output by that) and by multiplying the "theta" angle of the main exptab by -1. Hence the deliberately left multiplication by -1 at the end. FATE passes, and performance reports on other platforms/CPUs are welcome. Performance comparisons: iMDCT, PFA: 101127 decicycles in speed, 32765 runs, 3 skips iMDCT, Old: 211022 decicycles in speed, 32768 runs, 0 skips Standalone FFT, 300000 transforms of size 960: PFA Old FFT kiss_fft libfftw3f 3.659695s, 15.726912s, 13.300789s, 1.182222s Being only 3x slower than libfftw3f is a big achievement by itself. There appears to be something capping the performance in the iMDCT side of things, possibly during the pre-stage reindexing. However, it is certainly fast enough for now. Signed-off-by: Rostislav Pehlivanov <atomnuker@gmail.com>
2017-01-04 11:23:24 +02:00
}
s->fft15(s->tmp + s->ptwo_fft.revtab[i], fft15in, s->exptab, l_ptwo);
}
imdct15: replace the FFT with a faster PFA FFT algorithm This commit replaces the current inefficient non-power-of-two FFT with a much faster FFT based on the Prime Factor Algorithm. Although it is already much faster than the old algorithm without SIMD, the new algorithm makes use of the already very throughouly SIMD'd power of two FFT, which improves performance even more across all platforms which we have SIMD support for. Most of the work was done by Peter Barfuss, who passed the code to me to implement into the iMDCT and the current codebase. The code for a 5-point and 15-point FFT was derived from the previous implementation, although it was optimized and simplified, which will make its future SIMD easier. The 15-point FFT is currently using 6% of the current overall decoder overhead. The FFT can now easily be used as a forward transform by simply not multiplying the 5-point FFT's imaginary component by -1 (which comes from the fact that changing the complex exponential's angle by -1 also changes the output by that) and by multiplying the "theta" angle of the main exptab by -1. Hence the deliberately left multiplication by -1 at the end. FATE passes, and performance reports on other platforms/CPUs are welcome. Performance comparisons: iMDCT, PFA: 101127 decicycles in speed, 32765 runs, 3 skips iMDCT, Old: 211022 decicycles in speed, 32768 runs, 0 skips Standalone FFT, 300000 transforms of size 960: PFA Old FFT kiss_fft libfftw3f 3.659695s, 15.726912s, 13.300789s, 1.182222s Being only 3x slower than libfftw3f is a big achievement by itself. There appears to be something capping the performance in the iMDCT side of things, possibly during the pre-stage reindexing. However, it is certainly fast enough for now. Signed-off-by: Rostislav Pehlivanov <atomnuker@gmail.com>
2017-01-04 11:23:24 +02:00
/* Then a 15xN FFT (where N is a power of two) */
for (i = 0; i < 15; i++)
s->ptwo_fft.fft_calc(&s->ptwo_fft, s->tmp + l_ptwo*i);
/* Reindex again, apply twiddles and output */
s->postreindex(z, s->tmp, s->twiddle_exptab, s->pfa_postreindex, len8);
}
static void postrotate_c(FFTComplex *out, FFTComplex *in, FFTComplex *exp,
int *lut, ptrdiff_t len8)
{
int i;
imdct15: replace the FFT with a faster PFA FFT algorithm This commit replaces the current inefficient non-power-of-two FFT with a much faster FFT based on the Prime Factor Algorithm. Although it is already much faster than the old algorithm without SIMD, the new algorithm makes use of the already very throughouly SIMD'd power of two FFT, which improves performance even more across all platforms which we have SIMD support for. Most of the work was done by Peter Barfuss, who passed the code to me to implement into the iMDCT and the current codebase. The code for a 5-point and 15-point FFT was derived from the previous implementation, although it was optimized and simplified, which will make its future SIMD easier. The 15-point FFT is currently using 6% of the current overall decoder overhead. The FFT can now easily be used as a forward transform by simply not multiplying the 5-point FFT's imaginary component by -1 (which comes from the fact that changing the complex exponential's angle by -1 also changes the output by that) and by multiplying the "theta" angle of the main exptab by -1. Hence the deliberately left multiplication by -1 at the end. FATE passes, and performance reports on other platforms/CPUs are welcome. Performance comparisons: iMDCT, PFA: 101127 decicycles in speed, 32765 runs, 3 skips iMDCT, Old: 211022 decicycles in speed, 32768 runs, 0 skips Standalone FFT, 300000 transforms of size 960: PFA Old FFT kiss_fft libfftw3f 3.659695s, 15.726912s, 13.300789s, 1.182222s Being only 3x slower than libfftw3f is a big achievement by itself. There appears to be something capping the performance in the iMDCT side of things, possibly during the pre-stage reindexing. However, it is certainly fast enough for now. Signed-off-by: Rostislav Pehlivanov <atomnuker@gmail.com>
2017-01-04 11:23:24 +02:00
/* Reindex again, apply twiddles and output */
for (i = 0; i < len8; i++) {
imdct15: replace the FFT with a faster PFA FFT algorithm This commit replaces the current inefficient non-power-of-two FFT with a much faster FFT based on the Prime Factor Algorithm. Although it is already much faster than the old algorithm without SIMD, the new algorithm makes use of the already very throughouly SIMD'd power of two FFT, which improves performance even more across all platforms which we have SIMD support for. Most of the work was done by Peter Barfuss, who passed the code to me to implement into the iMDCT and the current codebase. The code for a 5-point and 15-point FFT was derived from the previous implementation, although it was optimized and simplified, which will make its future SIMD easier. The 15-point FFT is currently using 6% of the current overall decoder overhead. The FFT can now easily be used as a forward transform by simply not multiplying the 5-point FFT's imaginary component by -1 (which comes from the fact that changing the complex exponential's angle by -1 also changes the output by that) and by multiplying the "theta" angle of the main exptab by -1. Hence the deliberately left multiplication by -1 at the end. FATE passes, and performance reports on other platforms/CPUs are welcome. Performance comparisons: iMDCT, PFA: 101127 decicycles in speed, 32765 runs, 3 skips iMDCT, Old: 211022 decicycles in speed, 32768 runs, 0 skips Standalone FFT, 300000 transforms of size 960: PFA Old FFT kiss_fft libfftw3f 3.659695s, 15.726912s, 13.300789s, 1.182222s Being only 3x slower than libfftw3f is a big achievement by itself. There appears to be something capping the performance in the iMDCT side of things, possibly during the pre-stage reindexing. However, it is certainly fast enough for now. Signed-off-by: Rostislav Pehlivanov <atomnuker@gmail.com>
2017-01-04 11:23:24 +02:00
const int i0 = len8 + i, i1 = len8 - i - 1;
const int s0 = lut[i0], s1 = lut[i1];
imdct15: replace the FFT with a faster PFA FFT algorithm This commit replaces the current inefficient non-power-of-two FFT with a much faster FFT based on the Prime Factor Algorithm. Although it is already much faster than the old algorithm without SIMD, the new algorithm makes use of the already very throughouly SIMD'd power of two FFT, which improves performance even more across all platforms which we have SIMD support for. Most of the work was done by Peter Barfuss, who passed the code to me to implement into the iMDCT and the current codebase. The code for a 5-point and 15-point FFT was derived from the previous implementation, although it was optimized and simplified, which will make its future SIMD easier. The 15-point FFT is currently using 6% of the current overall decoder overhead. The FFT can now easily be used as a forward transform by simply not multiplying the 5-point FFT's imaginary component by -1 (which comes from the fact that changing the complex exponential's angle by -1 also changes the output by that) and by multiplying the "theta" angle of the main exptab by -1. Hence the deliberately left multiplication by -1 at the end. FATE passes, and performance reports on other platforms/CPUs are welcome. Performance comparisons: iMDCT, PFA: 101127 decicycles in speed, 32765 runs, 3 skips iMDCT, Old: 211022 decicycles in speed, 32768 runs, 0 skips Standalone FFT, 300000 transforms of size 960: PFA Old FFT kiss_fft libfftw3f 3.659695s, 15.726912s, 13.300789s, 1.182222s Being only 3x slower than libfftw3f is a big achievement by itself. There appears to be something capping the performance in the iMDCT side of things, possibly during the pre-stage reindexing. However, it is certainly fast enough for now. Signed-off-by: Rostislav Pehlivanov <atomnuker@gmail.com>
2017-01-04 11:23:24 +02:00
CMUL(out[i1].re, out[i0].im, in[s1].im, in[s1].re, exp[i1].im, exp[i1].re);
CMUL(out[i0].re, out[i1].im, in[s0].im, in[s0].re, exp[i0].im, exp[i0].re);
}
}
av_cold int ff_mdct15_init(MDCT15Context **ps, int inverse, int N, double scale)
{
MDCT15Context *s;
double alpha, theta;
int len2 = 15 * (1 << N);
int len = 2 * len2;
int i;
/* Tested and verified to work on everything in between */
if ((N < 2) || (N > 13))
return AVERROR(EINVAL);
s = av_mallocz(sizeof(*s));
if (!s)
return AVERROR(ENOMEM);
s->fft_n = N - 1;
s->len4 = len2 / 2;
s->len2 = len2;
s->inverse = inverse;
s->fft15 = fft15_c;
s->mdct = mdct15;
s->imdct_half = imdct15_half;
s->postreindex = postrotate_c;
if (ff_fft_init(&s->ptwo_fft, N - 1, s->inverse) < 0)
goto fail;
if (init_pfa_reindex_tabs(s))
goto fail;
s->tmp = av_malloc_array(len, 2 * sizeof(*s->tmp));
if (!s->tmp)
goto fail;
s->twiddle_exptab = av_malloc_array(s->len4, sizeof(*s->twiddle_exptab));
if (!s->twiddle_exptab)
goto fail;
theta = 0.125f + (scale < 0 ? s->len4 : 0);
scale = sqrt(fabs(scale));
for (i = 0; i < s->len4; i++) {
alpha = 2 * M_PI * (i + theta) / len;
s->twiddle_exptab[i].re = cosf(alpha) * scale;
s->twiddle_exptab[i].im = sinf(alpha) * scale;
}
/* 15-point FFT exptab */
for (i = 0; i < 19; i++) {
if (i < 15) {
double theta = (2.0f * M_PI * i) / 15.0f;
if (!s->inverse)
theta *= -1;
s->exptab[i].re = cosf(theta);
s->exptab[i].im = sinf(theta);
} else { /* Wrap around to simplify fft15 */
s->exptab[i] = s->exptab[i - 15];
}
}
/* 5-point FFT exptab */
s->exptab[19].re = cosf(2.0f * M_PI / 5.0f);
s->exptab[19].im = sinf(2.0f * M_PI / 5.0f);
s->exptab[20].re = cosf(1.0f * M_PI / 5.0f);
s->exptab[20].im = sinf(1.0f * M_PI / 5.0f);
/* Invert the phase for an inverse transform, do nothing for a forward transform */
if (s->inverse) {
s->exptab[19].im *= -1;
s->exptab[20].im *= -1;
}
#if ARCH_X86
ff_mdct15_init_x86(s);
#endif
*ps = s;
return 0;
fail:
ff_mdct15_uninit(&s);
return AVERROR(ENOMEM);
}