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FFmpeg/libavutil/tx_template.c

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lavu/tx: add support for double precision FFT and MDCT Simply moves and templates the actual transforms to support an additional data type. Unlike the float version, which is equal or better than libfftw3f, double precision output is bit identical with libfftw3.
2019-07-27 19:54:20 +02:00
/*
* Copyright (c) 2019 Lynne <dev@lynne.ee>
* Power of two FFT:
* Copyright (c) 2008 Loren Merritt
* Copyright (c) 2002 Fabrice Bellard
* Partly based on libdjbfft by D. J. Bernstein
*
* 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
*/
/* All costabs for a type are defined here */
COSTABLE(16);
COSTABLE(32);
COSTABLE(64);
COSTABLE(128);
COSTABLE(256);
COSTABLE(512);
COSTABLE(1024);
COSTABLE(2048);
COSTABLE(4096);
COSTABLE(8192);
COSTABLE(16384);
COSTABLE(32768);
COSTABLE(65536);
COSTABLE(131072);
DECLARE_ALIGNED(32, FFTComplex, TX_NAME(ff_cos_53))[4];
static FFTSample * const cos_tabs[18] = {
NULL,
NULL,
NULL,
NULL,
TX_NAME(ff_cos_16),
TX_NAME(ff_cos_32),
TX_NAME(ff_cos_64),
TX_NAME(ff_cos_128),
TX_NAME(ff_cos_256),
TX_NAME(ff_cos_512),
TX_NAME(ff_cos_1024),
TX_NAME(ff_cos_2048),
TX_NAME(ff_cos_4096),
TX_NAME(ff_cos_8192),
TX_NAME(ff_cos_16384),
TX_NAME(ff_cos_32768),
TX_NAME(ff_cos_65536),
TX_NAME(ff_cos_131072),
};
static av_always_inline void init_cos_tabs_idx(int index)
{
int m = 1 << index;
double freq = 2*M_PI/m;
FFTSample *tab = cos_tabs[index];
for(int i = 0; i <= m/4; i++)
lavu/tx: implement 32 bit fixed point FFT and MDCT Required minimal changes to the code so made sense to implement. FFT and MDCT tested, the output of both was properly rounded. Fun fact: the non-power-of-two fixed-point FFT and MDCT are the fastest ever non-power-of-two fixed-point FFT and MDCT written. This can replace the power of two integer MDCTs in aac and ac3 if the MIPS optimizations are ported across. Unfortunately the ac3 encoder uses a 16-bit fixed point forward transform, unlike the encoder which uses a 32bit inverse transform, so some modifications might be required there. The 3-point FFT is somewhat less accurate than it otherwise could be, having minor rounding errors with bigger transforms. However, this could be improved later, and the way its currently written is the way one would write assembly for it. Similar rounding errors can also be found throughout the power of two FFTs as well, though those are more difficult to correct. Despite this, the integer transforms are more than accurate enough.
2020-02-09 01:13:28 +02:00
tab[i] = RESCALE(cos(i*freq));
lavu/tx: add support for double precision FFT and MDCT Simply moves and templates the actual transforms to support an additional data type. Unlike the float version, which is equal or better than libfftw3f, double precision output is bit identical with libfftw3.
2019-07-27 19:54:20 +02:00
for(int i = 1; i < m/4; i++)
tab[m/2 - i] = tab[i];
}
#define INIT_FF_COS_TABS_FUNC(index, size) \
static av_cold void init_cos_tabs_ ## size (void) \
{ \
init_cos_tabs_idx(index); \
}
INIT_FF_COS_TABS_FUNC(4, 16)
INIT_FF_COS_TABS_FUNC(5, 32)
INIT_FF_COS_TABS_FUNC(6, 64)
INIT_FF_COS_TABS_FUNC(7, 128)
INIT_FF_COS_TABS_FUNC(8, 256)
INIT_FF_COS_TABS_FUNC(9, 512)
INIT_FF_COS_TABS_FUNC(10, 1024)
INIT_FF_COS_TABS_FUNC(11, 2048)
INIT_FF_COS_TABS_FUNC(12, 4096)
INIT_FF_COS_TABS_FUNC(13, 8192)
INIT_FF_COS_TABS_FUNC(14, 16384)
INIT_FF_COS_TABS_FUNC(15, 32768)
INIT_FF_COS_TABS_FUNC(16, 65536)
INIT_FF_COS_TABS_FUNC(17, 131072)
static av_cold void ff_init_53_tabs(void)
{
lavu/tx: implement 32 bit fixed point FFT and MDCT Required minimal changes to the code so made sense to implement. FFT and MDCT tested, the output of both was properly rounded. Fun fact: the non-power-of-two fixed-point FFT and MDCT are the fastest ever non-power-of-two fixed-point FFT and MDCT written. This can replace the power of two integer MDCTs in aac and ac3 if the MIPS optimizations are ported across. Unfortunately the ac3 encoder uses a 16-bit fixed point forward transform, unlike the encoder which uses a 32bit inverse transform, so some modifications might be required there. The 3-point FFT is somewhat less accurate than it otherwise could be, having minor rounding errors with bigger transforms. However, this could be improved later, and the way its currently written is the way one would write assembly for it. Similar rounding errors can also be found throughout the power of two FFTs as well, though those are more difficult to correct. Despite this, the integer transforms are more than accurate enough.
2020-02-09 01:13:28 +02:00
TX_NAME(ff_cos_53)[0] = (FFTComplex){ RESCALE(cos(2 * M_PI / 12)), RESCALE(cos(2 * M_PI / 12)) };
TX_NAME(ff_cos_53)[1] = (FFTComplex){ RESCALE(cos(2 * M_PI / 6)), RESCALE(cos(2 * M_PI / 6)) };
TX_NAME(ff_cos_53)[2] = (FFTComplex){ RESCALE(cos(2 * M_PI / 5)), RESCALE(sin(2 * M_PI / 5)) };
TX_NAME(ff_cos_53)[3] = (FFTComplex){ RESCALE(cos(2 * M_PI / 10)), RESCALE(sin(2 * M_PI / 10)) };
lavu/tx: add support for double precision FFT and MDCT Simply moves and templates the actual transforms to support an additional data type. Unlike the float version, which is equal or better than libfftw3f, double precision output is bit identical with libfftw3.
2019-07-27 19:54:20 +02:00
}
static CosTabsInitOnce cos_tabs_init_once[] = {
{ ff_init_53_tabs, AV_ONCE_INIT },
{ NULL },
{ NULL },
{ NULL },
{ init_cos_tabs_16, AV_ONCE_INIT },
{ init_cos_tabs_32, AV_ONCE_INIT },
{ init_cos_tabs_64, AV_ONCE_INIT },
{ init_cos_tabs_128, AV_ONCE_INIT },
{ init_cos_tabs_256, AV_ONCE_INIT },
{ init_cos_tabs_512, AV_ONCE_INIT },
{ init_cos_tabs_1024, AV_ONCE_INIT },
{ init_cos_tabs_2048, AV_ONCE_INIT },
{ init_cos_tabs_4096, AV_ONCE_INIT },
{ init_cos_tabs_8192, AV_ONCE_INIT },
{ init_cos_tabs_16384, AV_ONCE_INIT },
{ init_cos_tabs_32768, AV_ONCE_INIT },
{ init_cos_tabs_65536, AV_ONCE_INIT },
{ init_cos_tabs_131072, AV_ONCE_INIT },
};
static av_cold void init_cos_tabs(int index)
{
ff_thread_once(&cos_tabs_init_once[index].control,
cos_tabs_init_once[index].func);
}
static av_always_inline void fft3(FFTComplex *out, FFTComplex *in,
ptrdiff_t stride)
{
FFTComplex tmp[2];
lavu/tx: improve 3-point fixed precision There's just no reason not to when its so easy (albeit messy) and its also reducing the precision of all non-power-of-two transforms that use it.
2020-02-14 21:55:00 +02:00
#ifdef TX_INT32
int64_t mtmp[4];
#endif
lavu/tx: add support for double precision FFT and MDCT Simply moves and templates the actual transforms to support an additional data type. Unlike the float version, which is equal or better than libfftw3f, double precision output is bit identical with libfftw3.
2019-07-27 19:54:20 +02:00
lavu/tx: implement 32 bit fixed point FFT and MDCT Required minimal changes to the code so made sense to implement. FFT and MDCT tested, the output of both was properly rounded. Fun fact: the non-power-of-two fixed-point FFT and MDCT are the fastest ever non-power-of-two fixed-point FFT and MDCT written. This can replace the power of two integer MDCTs in aac and ac3 if the MIPS optimizations are ported across. Unfortunately the ac3 encoder uses a 16-bit fixed point forward transform, unlike the encoder which uses a 32bit inverse transform, so some modifications might be required there. The 3-point FFT is somewhat less accurate than it otherwise could be, having minor rounding errors with bigger transforms. However, this could be improved later, and the way its currently written is the way one would write assembly for it. Similar rounding errors can also be found throughout the power of two FFTs as well, though those are more difficult to correct. Despite this, the integer transforms are more than accurate enough.
2020-02-09 01:13:28 +02:00
BF(tmp[0].re, tmp[1].im, in[1].im, in[2].im);
BF(tmp[0].im, tmp[1].re, in[1].re, in[2].re);
lavu/tx: add support for double precision FFT and MDCT Simply moves and templates the actual transforms to support an additional data type. Unlike the float version, which is equal or better than libfftw3f, double precision output is bit identical with libfftw3.
2019-07-27 19:54:20 +02:00
out[0*stride].re = in[0].re + tmp[1].re;
out[0*stride].im = in[0].im + tmp[1].im;
lavu/tx: improve 3-point fixed precision There's just no reason not to when its so easy (albeit messy) and its also reducing the precision of all non-power-of-two transforms that use it.
2020-02-14 21:55:00 +02:00
#ifdef TX_INT32
mtmp[0] = (int64_t)TX_NAME(ff_cos_53)[0].re * tmp[0].re;
mtmp[1] = (int64_t)TX_NAME(ff_cos_53)[0].im * tmp[0].im;
mtmp[2] = (int64_t)TX_NAME(ff_cos_53)[1].re * tmp[1].re;
mtmp[3] = (int64_t)TX_NAME(ff_cos_53)[1].re * tmp[1].im;
out[1*stride].re = in[0].re - (mtmp[2] + mtmp[0] + 0x40000000 >> 31);
out[1*stride].im = in[0].im - (mtmp[3] - mtmp[1] + 0x40000000 >> 31);
out[2*stride].re = in[0].re - (mtmp[2] - mtmp[0] + 0x40000000 >> 31);
out[2*stride].im = in[0].im - (mtmp[3] + mtmp[1] + 0x40000000 >> 31);
#else
tmp[0].re = TX_NAME(ff_cos_53)[0].re * tmp[0].re;
tmp[0].im = TX_NAME(ff_cos_53)[0].im * tmp[0].im;
tmp[1].re = TX_NAME(ff_cos_53)[1].re * tmp[1].re;
tmp[1].im = TX_NAME(ff_cos_53)[1].re * tmp[1].im;
lavu/tx: add support for double precision FFT and MDCT Simply moves and templates the actual transforms to support an additional data type. Unlike the float version, which is equal or better than libfftw3f, double precision output is bit identical with libfftw3.
2019-07-27 19:54:20 +02:00
out[1*stride].re = in[0].re - tmp[1].re + tmp[0].re;
out[1*stride].im = in[0].im - tmp[1].im - tmp[0].im;
out[2*stride].re = in[0].re - tmp[1].re - tmp[0].re;
out[2*stride].im = in[0].im - tmp[1].im + tmp[0].im;
lavu/tx: improve 3-point fixed precision There's just no reason not to when its so easy (albeit messy) and its also reducing the precision of all non-power-of-two transforms that use it.
2020-02-14 21:55:00 +02:00
#endif
lavu/tx: add support for double precision FFT and MDCT Simply moves and templates the actual transforms to support an additional data type. Unlike the float version, which is equal or better than libfftw3f, double precision output is bit identical with libfftw3.
2019-07-27 19:54:20 +02:00
}
lavu/tx: implement 32 bit fixed point FFT and MDCT Required minimal changes to the code so made sense to implement. FFT and MDCT tested, the output of both was properly rounded. Fun fact: the non-power-of-two fixed-point FFT and MDCT are the fastest ever non-power-of-two fixed-point FFT and MDCT written. This can replace the power of two integer MDCTs in aac and ac3 if the MIPS optimizations are ported across. Unfortunately the ac3 encoder uses a 16-bit fixed point forward transform, unlike the encoder which uses a 32bit inverse transform, so some modifications might be required there. The 3-point FFT is somewhat less accurate than it otherwise could be, having minor rounding errors with bigger transforms. However, this could be improved later, and the way its currently written is the way one would write assembly for it. Similar rounding errors can also be found throughout the power of two FFTs as well, though those are more difficult to correct. Despite this, the integer transforms are more than accurate enough.
2020-02-09 01:13:28 +02:00
#define DECL_FFT5(NAME, D0, D1, D2, D3, D4) \
static av_always_inline void NAME(FFTComplex *out, FFTComplex *in, \
ptrdiff_t stride) \
{ \
FFTComplex z0[4], t[6]; \
\
BF(t[1].im, t[0].re, in[1].re, in[4].re); \
BF(t[1].re, t[0].im, in[1].im, in[4].im); \
BF(t[3].im, t[2].re, in[2].re, in[3].re); \
BF(t[3].re, t[2].im, in[2].im, in[3].im); \
\
lavu/tx: slightly optimize fft15 Saves 2 additions.
2020-02-10 19:37:34 +02:00
out[D0*stride].re = in[0].re + t[0].re + t[2].re; \
out[D0*stride].im = in[0].im + t[0].im + t[2].im; \
lavu/tx: implement 32 bit fixed point FFT and MDCT Required minimal changes to the code so made sense to implement. FFT and MDCT tested, the output of both was properly rounded. Fun fact: the non-power-of-two fixed-point FFT and MDCT are the fastest ever non-power-of-two fixed-point FFT and MDCT written. This can replace the power of two integer MDCTs in aac and ac3 if the MIPS optimizations are ported across. Unfortunately the ac3 encoder uses a 16-bit fixed point forward transform, unlike the encoder which uses a 32bit inverse transform, so some modifications might be required there. The 3-point FFT is somewhat less accurate than it otherwise could be, having minor rounding errors with bigger transforms. However, this could be improved later, and the way its currently written is the way one would write assembly for it. Similar rounding errors can also be found throughout the power of two FFTs as well, though those are more difficult to correct. Despite this, the integer transforms are more than accurate enough.
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\
SMUL(t[4].re, t[0].re, TX_NAME(ff_cos_53)[2].re, TX_NAME(ff_cos_53)[3].re, t[2].re, t[0].re); \
SMUL(t[4].im, t[0].im, TX_NAME(ff_cos_53)[2].re, TX_NAME(ff_cos_53)[3].re, t[2].im, t[0].im); \
CMUL(t[5].re, t[1].re, TX_NAME(ff_cos_53)[2].im, TX_NAME(ff_cos_53)[3].im, t[3].re, t[1].re); \
CMUL(t[5].im, t[1].im, TX_NAME(ff_cos_53)[2].im, TX_NAME(ff_cos_53)[3].im, t[3].im, t[1].im); \
\
BF(z0[0].re, z0[3].re, t[0].re, t[1].re); \
BF(z0[0].im, z0[3].im, t[0].im, t[1].im); \
BF(z0[2].re, z0[1].re, t[4].re, t[5].re); \
BF(z0[2].im, z0[1].im, t[4].im, t[5].im); \
\
out[D1*stride].re = in[0].re + z0[3].re; \
out[D1*stride].im = in[0].im + z0[0].im; \
out[D2*stride].re = in[0].re + z0[2].re; \
out[D2*stride].im = in[0].im + z0[1].im; \
out[D3*stride].re = in[0].re + z0[1].re; \
out[D3*stride].im = in[0].im + z0[2].im; \
out[D4*stride].re = in[0].re + z0[0].re; \
out[D4*stride].im = in[0].im + z0[3].im; \
lavu/tx: add support for double precision FFT and MDCT Simply moves and templates the actual transforms to support an additional data type. Unlike the float version, which is equal or better than libfftw3f, double precision output is bit identical with libfftw3.
2019-07-27 19:54:20 +02:00
}
DECL_FFT5(fft5, 0, 1, 2, 3, 4)
DECL_FFT5(fft5_m1, 0, 6, 12, 3, 9)
DECL_FFT5(fft5_m2, 10, 1, 7, 13, 4)
DECL_FFT5(fft5_m3, 5, 11, 2, 8, 14)
static av_always_inline void fft15(FFTComplex *out, FFTComplex *in,
ptrdiff_t stride)
{
FFTComplex tmp[15];
for (int i = 0; i < 5; i++)
fft3(tmp + i, in + i*3, 5);
fft5_m1(out, tmp + 0, stride);
fft5_m2(out, tmp + 5, stride);
fft5_m3(out, tmp + 10, stride);
}
#define BUTTERFLIES(a0,a1,a2,a3) {\
BF(t3, t5, t5, t1);\
BF(a2.re, a0.re, a0.re, t5);\
BF(a3.im, a1.im, a1.im, t3);\
BF(t4, t6, t2, t6);\
BF(a3.re, a1.re, a1.re, t4);\
BF(a2.im, a0.im, a0.im, t6);\
}
// force loading all the inputs before storing any.
// this is slightly slower for small data, but avoids store->load aliasing
// for addresses separated by large powers of 2.
#define BUTTERFLIES_BIG(a0,a1,a2,a3) {\
FFTSample r0=a0.re, i0=a0.im, r1=a1.re, i1=a1.im;\
BF(t3, t5, t5, t1);\
BF(a2.re, a0.re, r0, t5);\
BF(a3.im, a1.im, i1, t3);\
BF(t4, t6, t2, t6);\
BF(a3.re, a1.re, r1, t4);\
BF(a2.im, a0.im, i0, t6);\
}
#define TRANSFORM(a0,a1,a2,a3,wre,wim) {\
CMUL(t1, t2, a2.re, a2.im, wre, -wim);\
CMUL(t5, t6, a3.re, a3.im, wre, wim);\
BUTTERFLIES(a0,a1,a2,a3)\
}
#define TRANSFORM_ZERO(a0,a1,a2,a3) {\
t1 = a2.re;\
t2 = a2.im;\
t5 = a3.re;\
t6 = a3.im;\
BUTTERFLIES(a0,a1,a2,a3)\
}
/* z[0...8n-1], w[1...2n-1] */
#define PASS(name)\
static void name(FFTComplex *z, const FFTSample *wre, unsigned int n)\
{\
FFTSample t1, t2, t3, t4, t5, t6;\
int o1 = 2*n;\
int o2 = 4*n;\
int o3 = 6*n;\
const FFTSample *wim = wre+o1;\
n--;\
\
TRANSFORM_ZERO(z[0],z[o1],z[o2],z[o3]);\
TRANSFORM(z[1],z[o1+1],z[o2+1],z[o3+1],wre[1],wim[-1]);\
do {\
z += 2;\
wre += 2;\
wim -= 2;\
TRANSFORM(z[0],z[o1],z[o2],z[o3],wre[0],wim[0]);\
TRANSFORM(z[1],z[o1+1],z[o2+1],z[o3+1],wre[1],wim[-1]);\
} while(--n);\
}
PASS(pass)
#undef BUTTERFLIES
#define BUTTERFLIES BUTTERFLIES_BIG
PASS(pass_big)
#define DECL_FFT(n,n2,n4)\
static void fft##n(FFTComplex *z)\
{\
fft##n2(z);\
fft##n4(z+n4*2);\
fft##n4(z+n4*3);\
pass(z,TX_NAME(ff_cos_##n),n4/2);\
}
static void fft4(FFTComplex *z)
{
FFTSample t1, t2, t3, t4, t5, t6, t7, t8;
BF(t3, t1, z[0].re, z[1].re);
BF(t8, t6, z[3].re, z[2].re);
BF(z[2].re, z[0].re, t1, t6);
BF(t4, t2, z[0].im, z[1].im);
BF(t7, t5, z[2].im, z[3].im);
BF(z[3].im, z[1].im, t4, t8);
BF(z[3].re, z[1].re, t3, t7);
BF(z[2].im, z[0].im, t2, t5);
}
static void fft8(FFTComplex *z)
{
FFTSample t1, t2, t3, t4, t5, t6;
fft4(z);
BF(t1, z[5].re, z[4].re, -z[5].re);
BF(t2, z[5].im, z[4].im, -z[5].im);
BF(t5, z[7].re, z[6].re, -z[7].re);
BF(t6, z[7].im, z[6].im, -z[7].im);
BUTTERFLIES(z[0],z[2],z[4],z[6]);
lavu/tx: implement 32 bit fixed point FFT and MDCT Required minimal changes to the code so made sense to implement. FFT and MDCT tested, the output of both was properly rounded. Fun fact: the non-power-of-two fixed-point FFT and MDCT are the fastest ever non-power-of-two fixed-point FFT and MDCT written. This can replace the power of two integer MDCTs in aac and ac3 if the MIPS optimizations are ported across. Unfortunately the ac3 encoder uses a 16-bit fixed point forward transform, unlike the encoder which uses a 32bit inverse transform, so some modifications might be required there. The 3-point FFT is somewhat less accurate than it otherwise could be, having minor rounding errors with bigger transforms. However, this could be improved later, and the way its currently written is the way one would write assembly for it. Similar rounding errors can also be found throughout the power of two FFTs as well, though those are more difficult to correct. Despite this, the integer transforms are more than accurate enough.
2020-02-09 01:13:28 +02:00
TRANSFORM(z[1],z[3],z[5],z[7],RESCALE(M_SQRT1_2),RESCALE(M_SQRT1_2));
lavu/tx: add support for double precision FFT and MDCT Simply moves and templates the actual transforms to support an additional data type. Unlike the float version, which is equal or better than libfftw3f, double precision output is bit identical with libfftw3.
2019-07-27 19:54:20 +02:00
}
static void fft16(FFTComplex *z)
{
FFTSample t1, t2, t3, t4, t5, t6;
FFTSample cos_16_1 = TX_NAME(ff_cos_16)[1];
FFTSample cos_16_3 = TX_NAME(ff_cos_16)[3];
fft8(z);
fft4(z+8);
fft4(z+12);
TRANSFORM_ZERO(z[0],z[4],z[8],z[12]);
lavu/tx: implement 32 bit fixed point FFT and MDCT Required minimal changes to the code so made sense to implement. FFT and MDCT tested, the output of both was properly rounded. Fun fact: the non-power-of-two fixed-point FFT and MDCT are the fastest ever non-power-of-two fixed-point FFT and MDCT written. This can replace the power of two integer MDCTs in aac and ac3 if the MIPS optimizations are ported across. Unfortunately the ac3 encoder uses a 16-bit fixed point forward transform, unlike the encoder which uses a 32bit inverse transform, so some modifications might be required there. The 3-point FFT is somewhat less accurate than it otherwise could be, having minor rounding errors with bigger transforms. However, this could be improved later, and the way its currently written is the way one would write assembly for it. Similar rounding errors can also be found throughout the power of two FFTs as well, though those are more difficult to correct. Despite this, the integer transforms are more than accurate enough.
2020-02-09 01:13:28 +02:00
TRANSFORM(z[2],z[6],z[10],z[14],RESCALE(M_SQRT1_2),RESCALE(M_SQRT1_2));
lavu/tx: add support for double precision FFT and MDCT Simply moves and templates the actual transforms to support an additional data type. Unlike the float version, which is equal or better than libfftw3f, double precision output is bit identical with libfftw3.
2019-07-27 19:54:20 +02:00
TRANSFORM(z[1],z[5],z[9],z[13],cos_16_1,cos_16_3);
TRANSFORM(z[3],z[7],z[11],z[15],cos_16_3,cos_16_1);
}
DECL_FFT(32,16,8)
DECL_FFT(64,32,16)
DECL_FFT(128,64,32)
DECL_FFT(256,128,64)
DECL_FFT(512,256,128)
#define pass pass_big
DECL_FFT(1024,512,256)
DECL_FFT(2048,1024,512)
DECL_FFT(4096,2048,1024)
DECL_FFT(8192,4096,2048)
DECL_FFT(16384,8192,4096)
DECL_FFT(32768,16384,8192)
DECL_FFT(65536,32768,16384)
DECL_FFT(131072,65536,32768)
static void (* const fft_dispatch[])(FFTComplex*) = {
fft4, fft8, fft16, fft32, fft64, fft128, fft256, fft512, fft1024,
fft2048, fft4096, fft8192, fft16384, fft32768, fft65536, fft131072
};
#define DECL_COMP_FFT(N) \
static void compound_fft_##N##xM(AVTXContext *s, void *_out, \
void *_in, ptrdiff_t stride) \
{ \
const int m = s->m, *in_map = s->pfatab, *out_map = in_map + N*m; \
FFTComplex *in = _in; \
FFTComplex *out = _out; \
FFTComplex fft##N##in[N]; \
void (*fftp)(FFTComplex *z) = fft_dispatch[av_log2(m) - 2]; \
\
for (int i = 0; i < m; i++) { \
for (int j = 0; j < N; j++) \
fft##N##in[j] = in[in_map[i*N + j]]; \
fft##N(s->tmp + s->revtab[i], fft##N##in, m); \
} \
\
for (int i = 0; i < N; i++) \
fftp(s->tmp + m*i); \
\
for (int i = 0; i < N*m; i++) \
out[i] = s->tmp[out_map[i]]; \
}
DECL_COMP_FFT(3)
DECL_COMP_FFT(5)
DECL_COMP_FFT(15)
static void monolithic_fft(AVTXContext *s, void *_out, void *_in,
ptrdiff_t stride)
{
FFTComplex *in = _in;
FFTComplex *out = _out;
int m = s->m, mb = av_log2(m) - 2;
for (int i = 0; i < m; i++)
out[s->revtab[i]] = in[i];
fft_dispatch[mb](out);
}
#define DECL_COMP_IMDCT(N) \
static void compound_imdct_##N##xM(AVTXContext *s, void *_dst, void *_src, \
ptrdiff_t stride) \
{ \
FFTComplex fft##N##in[N]; \
FFTComplex *z = _dst, *exp = s->exptab; \
const int m = s->m, len8 = N*m >> 1; \
const int *in_map = s->pfatab, *out_map = in_map + N*m; \
const FFTSample *src = _src, *in1, *in2; \
void (*fftp)(FFTComplex *) = fft_dispatch[av_log2(m) - 2]; \
\
stride /= sizeof(*src); /* To convert it from bytes */ \
in1 = src; \
in2 = src + ((N*m*2) - 1) * stride; \
\
for (int i = 0; i < m; i++) { \
for (int j = 0; j < N; j++) { \
const int k = in_map[i*N + j]; \
FFTComplex tmp = { in2[-k*stride], in1[k*stride] }; \
CMUL3(fft##N##in[j], tmp, exp[k >> 1]); \
} \
fft##N(s->tmp + s->revtab[i], fft##N##in, m); \
} \
\
for (int i = 0; i < N; i++) \
fftp(s->tmp + m*i); \
\
for (int i = 0; i < len8; i++) { \
const int i0 = len8 + i, i1 = len8 - i - 1; \
const int s0 = out_map[i0], s1 = out_map[i1]; \
FFTComplex src1 = { s->tmp[s1].im, s->tmp[s1].re }; \
FFTComplex src0 = { s->tmp[s0].im, s->tmp[s0].re }; \
\
CMUL(z[i1].re, z[i0].im, src1.re, src1.im, exp[i1].im, exp[i1].re); \
CMUL(z[i0].re, z[i1].im, src0.re, src0.im, exp[i0].im, exp[i0].re); \
} \
}
DECL_COMP_IMDCT(3)
DECL_COMP_IMDCT(5)
DECL_COMP_IMDCT(15)
#define DECL_COMP_MDCT(N) \
static void compound_mdct_##N##xM(AVTXContext *s, void *_dst, void *_src, \
ptrdiff_t stride) \
{ \
FFTSample *src = _src, *dst = _dst; \
FFTComplex *exp = s->exptab, tmp, fft##N##in[N]; \
const int m = s->m, len4 = N*m, len3 = len4 * 3, len8 = len4 >> 1; \
const int *in_map = s->pfatab, *out_map = in_map + N*m; \
void (*fftp)(FFTComplex *) = fft_dispatch[av_log2(m) - 2]; \
\
stride /= sizeof(*dst); \
\
for (int i = 0; i < m; i++) { /* Folding and pre-reindexing */ \
for (int j = 0; j < N; j++) { \
const int k = in_map[i*N + j]; \
if (k < len4) { \
lavu/tx: implement 32 bit fixed point FFT and MDCT Required minimal changes to the code so made sense to implement. FFT and MDCT tested, the output of both was properly rounded. Fun fact: the non-power-of-two fixed-point FFT and MDCT are the fastest ever non-power-of-two fixed-point FFT and MDCT written. This can replace the power of two integer MDCTs in aac and ac3 if the MIPS optimizations are ported across. Unfortunately the ac3 encoder uses a 16-bit fixed point forward transform, unlike the encoder which uses a 32bit inverse transform, so some modifications might be required there. The 3-point FFT is somewhat less accurate than it otherwise could be, having minor rounding errors with bigger transforms. However, this could be improved later, and the way its currently written is the way one would write assembly for it. Similar rounding errors can also be found throughout the power of two FFTs as well, though those are more difficult to correct. Despite this, the integer transforms are more than accurate enough.
2020-02-09 01:13:28 +02:00
tmp.re = FOLD(-src[ len4 + k], src[1*len4 - 1 - k]); \
tmp.im = FOLD(-src[ len3 + k], -src[1*len3 - 1 - k]); \
lavu/tx: add support for double precision FFT and MDCT Simply moves and templates the actual transforms to support an additional data type. Unlike the float version, which is equal or better than libfftw3f, double precision output is bit identical with libfftw3.
2019-07-27 19:54:20 +02:00
} else { \
lavu/tx: implement 32 bit fixed point FFT and MDCT Required minimal changes to the code so made sense to implement. FFT and MDCT tested, the output of both was properly rounded. Fun fact: the non-power-of-two fixed-point FFT and MDCT are the fastest ever non-power-of-two fixed-point FFT and MDCT written. This can replace the power of two integer MDCTs in aac and ac3 if the MIPS optimizations are ported across. Unfortunately the ac3 encoder uses a 16-bit fixed point forward transform, unlike the encoder which uses a 32bit inverse transform, so some modifications might be required there. The 3-point FFT is somewhat less accurate than it otherwise could be, having minor rounding errors with bigger transforms. However, this could be improved later, and the way its currently written is the way one would write assembly for it. Similar rounding errors can also be found throughout the power of two FFTs as well, though those are more difficult to correct. Despite this, the integer transforms are more than accurate enough.
2020-02-09 01:13:28 +02:00
tmp.re = FOLD(-src[ len4 + k], -src[5*len4 - 1 - k]); \
tmp.im = FOLD( src[-len4 + k], -src[1*len3 - 1 - k]); \
lavu/tx: add support for double precision FFT and MDCT Simply moves and templates the actual transforms to support an additional data type. Unlike the float version, which is equal or better than libfftw3f, double precision output is bit identical with libfftw3.
2019-07-27 19:54:20 +02:00
} \
CMUL(fft##N##in[j].im, fft##N##in[j].re, tmp.re, tmp.im, \
exp[k >> 1].re, exp[k >> 1].im); \
} \
fft##N(s->tmp + s->revtab[i], fft##N##in, m); \
} \
\
for (int i = 0; i < N; i++) \
fftp(s->tmp + m*i); \
\
for (int i = 0; i < len8; i++) { \
const int i0 = len8 + i, i1 = len8 - i - 1; \
const int s0 = out_map[i0], s1 = out_map[i1]; \
FFTComplex src1 = { s->tmp[s1].re, s->tmp[s1].im }; \
FFTComplex src0 = { s->tmp[s0].re, s->tmp[s0].im }; \
\
CMUL(dst[2*i1*stride + stride], dst[2*i0*stride], src0.re, src0.im, \
exp[i0].im, exp[i0].re); \
CMUL(dst[2*i0*stride + stride], dst[2*i1*stride], src1.re, src1.im, \
exp[i1].im, exp[i1].re); \
} \
}
DECL_COMP_MDCT(3)
DECL_COMP_MDCT(5)
DECL_COMP_MDCT(15)
static void monolithic_imdct(AVTXContext *s, void *_dst, void *_src,
ptrdiff_t stride)
{
FFTComplex *z = _dst, *exp = s->exptab;
const int m = s->m, len8 = m >> 1;
const FFTSample *src = _src, *in1, *in2;
void (*fftp)(FFTComplex *) = fft_dispatch[av_log2(m) - 2];
stride /= sizeof(*src);
in1 = src;
in2 = src + ((m*2) - 1) * stride;
for (int i = 0; i < m; i++) {
FFTComplex tmp = { in2[-2*i*stride], in1[2*i*stride] };
CMUL3(z[s->revtab[i]], tmp, exp[i]);
}
fftp(z);
for (int i = 0; i < len8; i++) {
const int i0 = len8 + i, i1 = len8 - i - 1;
FFTComplex src1 = { z[i1].im, z[i1].re };
FFTComplex src0 = { z[i0].im, z[i0].re };
CMUL(z[i1].re, z[i0].im, src1.re, src1.im, exp[i1].im, exp[i1].re);
CMUL(z[i0].re, z[i1].im, src0.re, src0.im, exp[i0].im, exp[i0].re);
}
}
static void monolithic_mdct(AVTXContext *s, void *_dst, void *_src,
ptrdiff_t stride)
{
FFTSample *src = _src, *dst = _dst;
FFTComplex *exp = s->exptab, tmp, *z = _dst;
const int m = s->m, len4 = m, len3 = len4 * 3, len8 = len4 >> 1;
void (*fftp)(FFTComplex *) = fft_dispatch[av_log2(m) - 2];
stride /= sizeof(*dst);
for (int i = 0; i < m; i++) { /* Folding and pre-reindexing */
const int k = 2*i;
if (k < len4) {
lavu/tx: implement 32 bit fixed point FFT and MDCT Required minimal changes to the code so made sense to implement. FFT and MDCT tested, the output of both was properly rounded. Fun fact: the non-power-of-two fixed-point FFT and MDCT are the fastest ever non-power-of-two fixed-point FFT and MDCT written. This can replace the power of two integer MDCTs in aac and ac3 if the MIPS optimizations are ported across. Unfortunately the ac3 encoder uses a 16-bit fixed point forward transform, unlike the encoder which uses a 32bit inverse transform, so some modifications might be required there. The 3-point FFT is somewhat less accurate than it otherwise could be, having minor rounding errors with bigger transforms. However, this could be improved later, and the way its currently written is the way one would write assembly for it. Similar rounding errors can also be found throughout the power of two FFTs as well, though those are more difficult to correct. Despite this, the integer transforms are more than accurate enough.
2020-02-09 01:13:28 +02:00
tmp.re = FOLD(-src[ len4 + k], src[1*len4 - 1 - k]);
tmp.im = FOLD(-src[ len3 + k], -src[1*len3 - 1 - k]);
lavu/tx: add support for double precision FFT and MDCT Simply moves and templates the actual transforms to support an additional data type. Unlike the float version, which is equal or better than libfftw3f, double precision output is bit identical with libfftw3.
2019-07-27 19:54:20 +02:00
} else {
lavu/tx: implement 32 bit fixed point FFT and MDCT Required minimal changes to the code so made sense to implement. FFT and MDCT tested, the output of both was properly rounded. Fun fact: the non-power-of-two fixed-point FFT and MDCT are the fastest ever non-power-of-two fixed-point FFT and MDCT written. This can replace the power of two integer MDCTs in aac and ac3 if the MIPS optimizations are ported across. Unfortunately the ac3 encoder uses a 16-bit fixed point forward transform, unlike the encoder which uses a 32bit inverse transform, so some modifications might be required there. The 3-point FFT is somewhat less accurate than it otherwise could be, having minor rounding errors with bigger transforms. However, this could be improved later, and the way its currently written is the way one would write assembly for it. Similar rounding errors can also be found throughout the power of two FFTs as well, though those are more difficult to correct. Despite this, the integer transforms are more than accurate enough.
2020-02-09 01:13:28 +02:00
tmp.re = FOLD(-src[ len4 + k], -src[5*len4 - 1 - k]);
tmp.im = FOLD( src[-len4 + k], -src[1*len3 - 1 - k]);
lavu/tx: add support for double precision FFT and MDCT Simply moves and templates the actual transforms to support an additional data type. Unlike the float version, which is equal or better than libfftw3f, double precision output is bit identical with libfftw3.
2019-07-27 19:54:20 +02:00
}
CMUL(z[s->revtab[i]].im, z[s->revtab[i]].re, tmp.re, tmp.im,
exp[i].re, exp[i].im);
}
fftp(z);
for (int i = 0; i < len8; i++) {
const int i0 = len8 + i, i1 = len8 - i - 1;
FFTComplex src1 = { z[i1].re, z[i1].im };
FFTComplex src0 = { z[i0].re, z[i0].im };
CMUL(dst[2*i1*stride + stride], dst[2*i0*stride], src0.re, src0.im,
exp[i0].im, exp[i0].re);
CMUL(dst[2*i0*stride + stride], dst[2*i1*stride], src1.re, src1.im,
exp[i1].im, exp[i1].re);
}
}
static int gen_mdct_exptab(AVTXContext *s, int len4, double scale)
{
const double theta = (scale < 0 ? len4 : 0) + 1.0/8.0;
if (!(s->exptab = av_malloc_array(len4, sizeof(*s->exptab))))
return AVERROR(ENOMEM);
scale = sqrt(fabs(scale));
for (int i = 0; i < len4; i++) {
const double alpha = M_PI_2 * (i + theta) / len4;
lavu/tx: implement 32 bit fixed point FFT and MDCT Required minimal changes to the code so made sense to implement. FFT and MDCT tested, the output of both was properly rounded. Fun fact: the non-power-of-two fixed-point FFT and MDCT are the fastest ever non-power-of-two fixed-point FFT and MDCT written. This can replace the power of two integer MDCTs in aac and ac3 if the MIPS optimizations are ported across. Unfortunately the ac3 encoder uses a 16-bit fixed point forward transform, unlike the encoder which uses a 32bit inverse transform, so some modifications might be required there. The 3-point FFT is somewhat less accurate than it otherwise could be, having minor rounding errors with bigger transforms. However, this could be improved later, and the way its currently written is the way one would write assembly for it. Similar rounding errors can also be found throughout the power of two FFTs as well, though those are more difficult to correct. Despite this, the integer transforms are more than accurate enough.
2020-02-09 01:13:28 +02:00
s->exptab[i].re = RESCALE(cos(alpha) * scale);
s->exptab[i].im = RESCALE(sin(alpha) * scale);
lavu/tx: add support for double precision FFT and MDCT Simply moves and templates the actual transforms to support an additional data type. Unlike the float version, which is equal or better than libfftw3f, double precision output is bit identical with libfftw3.
2019-07-27 19:54:20 +02:00
}
return 0;
}
int TX_NAME(ff_tx_init_mdct_fft)(AVTXContext *s, av_tx_fn *tx,
enum AVTXType type, int inv, int len,
const void *scale, uint64_t flags)
{
lavu/tx: implement 32 bit fixed point FFT and MDCT Required minimal changes to the code so made sense to implement. FFT and MDCT tested, the output of both was properly rounded. Fun fact: the non-power-of-two fixed-point FFT and MDCT are the fastest ever non-power-of-two fixed-point FFT and MDCT written. This can replace the power of two integer MDCTs in aac and ac3 if the MIPS optimizations are ported across. Unfortunately the ac3 encoder uses a 16-bit fixed point forward transform, unlike the encoder which uses a 32bit inverse transform, so some modifications might be required there. The 3-point FFT is somewhat less accurate than it otherwise could be, having minor rounding errors with bigger transforms. However, this could be improved later, and the way its currently written is the way one would write assembly for it. Similar rounding errors can also be found throughout the power of two FFTs as well, though those are more difficult to correct. Despite this, the integer transforms are more than accurate enough.
2020-02-09 01:13:28 +02:00
const int is_mdct = ff_tx_type_is_mdct(type);
lavu/tx: add support for double precision FFT and MDCT Simply moves and templates the actual transforms to support an additional data type. Unlike the float version, which is equal or better than libfftw3f, double precision output is bit identical with libfftw3.
2019-07-27 19:54:20 +02:00
int err, n = 1, m = 1, max_ptwo = 1 << (FF_ARRAY_ELEMS(fft_dispatch) + 1);
if (is_mdct)
len >>= 1;
#define CHECK_FACTOR(DST, FACTOR, SRC) \
if (DST == 1 && !(SRC % FACTOR)) { \
DST = FACTOR; \
SRC /= FACTOR; \
}
CHECK_FACTOR(n, 15, len)
CHECK_FACTOR(n, 5, len)
CHECK_FACTOR(n, 3, len)
lavu/tx: undef the correct macro It was renamed and no warning was given for undeffing a nonexisting one.
2020-02-10 19:36:45 +02:00
#undef CHECK_FACTOR
lavu/tx: add support for double precision FFT and MDCT Simply moves and templates the actual transforms to support an additional data type. Unlike the float version, which is equal or better than libfftw3f, double precision output is bit identical with libfftw3.
2019-07-27 19:54:20 +02:00
/* len must be a power of two now */
if (!(len & (len - 1)) && len >= 4 && len <= max_ptwo) {
m = len;
len = 1;
}
s->n = n;
s->m = m;
s->inv = inv;
s->type = type;
/* Filter out direct 3, 5 and 15 transforms, too niche */
if (len > 1 || m == 1) {
av_log(NULL, AV_LOG_ERROR, "Unsupported transform size: n = %i, "
"m = %i, residual = %i!\n", n, m, len);
return AVERROR(EINVAL);
} else if (n > 1 && m > 1) { /* 2D transform case */
if ((err = ff_tx_gen_compound_mapping(s)))
return err;
if (!(s->tmp = av_malloc(n*m*sizeof(*s->tmp))))
return AVERROR(ENOMEM);
*tx = n == 3 ? compound_fft_3xM :
n == 5 ? compound_fft_5xM :
compound_fft_15xM;
if (is_mdct)
*tx = n == 3 ? inv ? compound_imdct_3xM : compound_mdct_3xM :
n == 5 ? inv ? compound_imdct_5xM : compound_mdct_5xM :
inv ? compound_imdct_15xM : compound_mdct_15xM;
} else { /* Direct transform case */
*tx = monolithic_fft;
if (is_mdct)
*tx = inv ? monolithic_imdct : monolithic_mdct;
}
if (n != 1)
init_cos_tabs(0);
if (m != 1) {
ff_tx_gen_ptwo_revtab(s);
for (int i = 4; i <= av_log2(m); i++)
init_cos_tabs(i);
}
if (is_mdct)
lavu/tx: implement 32 bit fixed point FFT and MDCT Required minimal changes to the code so made sense to implement. FFT and MDCT tested, the output of both was properly rounded. Fun fact: the non-power-of-two fixed-point FFT and MDCT are the fastest ever non-power-of-two fixed-point FFT and MDCT written. This can replace the power of two integer MDCTs in aac and ac3 if the MIPS optimizations are ported across. Unfortunately the ac3 encoder uses a 16-bit fixed point forward transform, unlike the encoder which uses a 32bit inverse transform, so some modifications might be required there. The 3-point FFT is somewhat less accurate than it otherwise could be, having minor rounding errors with bigger transforms. However, this could be improved later, and the way its currently written is the way one would write assembly for it. Similar rounding errors can also be found throughout the power of two FFTs as well, though those are more difficult to correct. Despite this, the integer transforms are more than accurate enough.
2020-02-09 01:13:28 +02:00
return gen_mdct_exptab(s, n*m, *((SCALE_TYPE *)scale));
lavu/tx: add support for double precision FFT and MDCT Simply moves and templates the actual transforms to support an additional data type. Unlike the float version, which is equal or better than libfftw3f, double precision output is bit identical with libfftw3.
2019-07-27 19:54:20 +02:00
return 0;
}
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