The code relies on their validity and otherwise can try to access a NULL
object->rle pointer, causing segmentation faults.
Reviewed-by: Michael Niedermayer <michael@niedermayer.cc>
Signed-off-by: Andreas Cadhalpun <Andreas.Cadhalpun@googlemail.com>
The assumption this is based on is wrong, the code is not always run with bitexact flags
This reverts commit a956164e1e, reversing
changes made to f6005907fd.
Approved-by: James Almer <jamrial@gmail.com>
Fixes out of array access
Fixes: 452/fuzz-1-ffmpeg_VIDEO_AV_CODEC_ID_INTERPLAY_VIDEO_fuzzer
Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/targets/ffmpeg
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
This work is sponsored by, and copyright, Google.
This is similar to the arm version, but due to the larger registers
on aarch64, we can do 8 pixels at a time for all filter sizes.
Examples of runtimes vs the 32 bit version, on a Cortex A53:
ARM AArch64
vp9_loop_filter_h_4_8_10bpp_neon: 213.2 172.6
vp9_loop_filter_h_8_8_10bpp_neon: 281.2 244.2
vp9_loop_filter_h_16_8_10bpp_neon: 657.0 444.5
vp9_loop_filter_h_16_16_10bpp_neon: 1280.4 877.7
vp9_loop_filter_mix2_h_44_16_10bpp_neon: 397.7 358.0
vp9_loop_filter_mix2_h_48_16_10bpp_neon: 465.7 429.0
vp9_loop_filter_mix2_h_84_16_10bpp_neon: 465.7 428.0
vp9_loop_filter_mix2_h_88_16_10bpp_neon: 533.7 499.0
vp9_loop_filter_mix2_v_44_16_10bpp_neon: 271.5 244.0
vp9_loop_filter_mix2_v_48_16_10bpp_neon: 330.0 305.0
vp9_loop_filter_mix2_v_84_16_10bpp_neon: 329.0 306.0
vp9_loop_filter_mix2_v_88_16_10bpp_neon: 386.0 365.0
vp9_loop_filter_v_4_8_10bpp_neon: 150.0 115.2
vp9_loop_filter_v_8_8_10bpp_neon: 209.0 175.5
vp9_loop_filter_v_16_8_10bpp_neon: 492.7 345.2
vp9_loop_filter_v_16_16_10bpp_neon: 951.0 682.7
This is significantly faster than the ARM version in almost
all cases except for the mix2 functions.
Based on START_TIMER/STOP_TIMER wrapping around a few individual
functions, the speedup vs C code is around 2-3x.
Signed-off-by: Martin Storsjö <martin@martin.st>
This work is sponsored by, and copyright, Google.
Compared to the arm version, on aarch64 we can keep the full 8x8
transform in registers, and for 16x16 and 32x32, we can process
it in slices of 4 pixels instead of 2.
Examples of runtimes vs the 32 bit version, on a Cortex A53:
ARM AArch64
vp9_inv_adst_adst_4x4_sub4_add_10_neon: 111.0 109.7
vp9_inv_adst_adst_8x8_sub8_add_10_neon: 914.0 733.5
vp9_inv_adst_adst_16x16_sub16_add_10_neon: 5184.0 3745.7
vp9_inv_dct_dct_4x4_sub1_add_10_neon: 65.0 65.7
vp9_inv_dct_dct_4x4_sub4_add_10_neon: 100.0 96.7
vp9_inv_dct_dct_8x8_sub1_add_10_neon: 111.0 119.7
vp9_inv_dct_dct_8x8_sub8_add_10_neon: 618.0 494.7
vp9_inv_dct_dct_16x16_sub1_add_10_neon: 295.1 284.6
vp9_inv_dct_dct_16x16_sub2_add_10_neon: 2303.2 1883.9
vp9_inv_dct_dct_16x16_sub8_add_10_neon: 2984.8 2189.3
vp9_inv_dct_dct_16x16_sub16_add_10_neon: 3890.0 2799.4
vp9_inv_dct_dct_32x32_sub1_add_10_neon: 1044.4 1012.7
vp9_inv_dct_dct_32x32_sub2_add_10_neon: 13333.7 9695.1
vp9_inv_dct_dct_32x32_sub16_add_10_neon: 18531.3 12459.8
vp9_inv_dct_dct_32x32_sub32_add_10_neon: 24470.7 16160.2
vp9_inv_wht_wht_4x4_sub4_add_10_neon: 83.0 79.7
The larger transforms are significantly faster than the corresponding
ARM versions.
The speedup vs C code is smaller than in 32 bit mode, probably
because the 64 bit intermediates in the C code can be expressed
more efficiently in aarch64.
Signed-off-by: Martin Storsjö <martin@martin.st>
This work is sponsored by, and copyright, Google.
This has mostly got the same differences to the 8 bit version as
in the arm version. For the horizontal filters, we do 16 pixels
in parallel as well. For the 8 pixel wide vertical filters, we can
accumulate 4 rows before storing, just as in the 8 bit version.
Examples of runtimes vs the 32 bit version, on a Cortex A53:
ARM AArch64
vp9_avg4_10bpp_neon: 35.7 30.7
vp9_avg8_10bpp_neon: 93.5 84.7
vp9_avg16_10bpp_neon: 324.4 296.6
vp9_avg32_10bpp_neon: 1236.5 1148.2
vp9_avg64_10bpp_neon: 4639.6 4571.1
vp9_avg_8tap_smooth_4h_10bpp_neon: 130.0 128.0
vp9_avg_8tap_smooth_4hv_10bpp_neon: 440.0 440.5
vp9_avg_8tap_smooth_4v_10bpp_neon: 114.0 105.5
vp9_avg_8tap_smooth_8h_10bpp_neon: 327.0 314.0
vp9_avg_8tap_smooth_8hv_10bpp_neon: 918.7 865.4
vp9_avg_8tap_smooth_8v_10bpp_neon: 330.0 300.2
vp9_avg_8tap_smooth_16h_10bpp_neon: 1187.5 1155.5
vp9_avg_8tap_smooth_16hv_10bpp_neon: 2663.1 2591.0
vp9_avg_8tap_smooth_16v_10bpp_neon: 1107.4 1078.3
vp9_avg_8tap_smooth_64h_10bpp_neon: 17754.6 17454.7
vp9_avg_8tap_smooth_64hv_10bpp_neon: 33285.2 33001.5
vp9_avg_8tap_smooth_64v_10bpp_neon: 16066.9 16048.6
vp9_put4_10bpp_neon: 25.5 21.7
vp9_put8_10bpp_neon: 56.0 52.0
vp9_put16_10bpp_neon/armv8: 183.0 163.1
vp9_put32_10bpp_neon/armv8: 678.6 563.1
vp9_put64_10bpp_neon/armv8: 2679.9 2195.8
vp9_put_8tap_smooth_4h_10bpp_neon: 120.0 118.0
vp9_put_8tap_smooth_4hv_10bpp_neon: 435.2 435.0
vp9_put_8tap_smooth_4v_10bpp_neon: 107.0 98.2
vp9_put_8tap_smooth_8h_10bpp_neon: 303.0 290.0
vp9_put_8tap_smooth_8hv_10bpp_neon: 893.7 828.7
vp9_put_8tap_smooth_8v_10bpp_neon: 305.5 263.5
vp9_put_8tap_smooth_16h_10bpp_neon: 1089.1 1059.2
vp9_put_8tap_smooth_16hv_10bpp_neon: 2578.8 2452.4
vp9_put_8tap_smooth_16v_10bpp_neon: 1009.5 933.5
vp9_put_8tap_smooth_64h_10bpp_neon: 16223.4 15918.6
vp9_put_8tap_smooth_64hv_10bpp_neon: 32153.0 31016.2
vp9_put_8tap_smooth_64v_10bpp_neon: 14516.5 13748.1
These are generally about as fast as the corresponding ARM
routines on the same CPU (at least on the A53), in most cases
marginally faster.
The speedup vs C code is around 4-9x.
Signed-off-by: Martin Storsjö <martin@martin.st>
This work is sponsored by, and copyright, Google.
This is more in line with how it will be extended for more bitdepths.
Signed-off-by: Martin Storsjö <martin@martin.st>
This work is sponsored by, and copyright, Google.
This is pretty much similar to the 8 bpp version, but in some senses
simpler. All input pixels are 16 bits, and all intermediates also fit
in 16 bits, so there's no lengthening/narrowing in the filter at all.
For the full 16 pixel wide filter, we can only process 4 pixels at a time
(using an implementation very much similar to the one for 8 bpp),
but we can do 8 pixels at a time for the 4 and 8 pixel wide filters with
a different implementation of the core filter.
Examples of relative speedup compared to the C version, from checkasm:
Cortex A7 A8 A9 A53
vp9_loop_filter_h_4_8_10bpp_neon: 1.83 2.16 1.40 2.09
vp9_loop_filter_h_8_8_10bpp_neon: 1.39 1.67 1.24 1.70
vp9_loop_filter_h_16_8_10bpp_neon: 1.56 1.47 1.10 1.81
vp9_loop_filter_h_16_16_10bpp_neon: 1.94 1.69 1.33 2.24
vp9_loop_filter_mix2_h_44_16_10bpp_neon: 2.01 2.27 1.67 2.39
vp9_loop_filter_mix2_h_48_16_10bpp_neon: 1.84 2.06 1.45 2.19
vp9_loop_filter_mix2_h_84_16_10bpp_neon: 1.89 2.20 1.47 2.29
vp9_loop_filter_mix2_h_88_16_10bpp_neon: 1.69 2.12 1.47 2.08
vp9_loop_filter_mix2_v_44_16_10bpp_neon: 3.16 3.98 2.50 4.05
vp9_loop_filter_mix2_v_48_16_10bpp_neon: 2.84 3.64 2.25 3.77
vp9_loop_filter_mix2_v_84_16_10bpp_neon: 2.65 3.45 2.16 3.54
vp9_loop_filter_mix2_v_88_16_10bpp_neon: 2.55 3.30 2.16 3.55
vp9_loop_filter_v_4_8_10bpp_neon: 2.85 3.97 2.24 3.68
vp9_loop_filter_v_8_8_10bpp_neon: 2.27 3.19 1.96 3.08
vp9_loop_filter_v_16_8_10bpp_neon: 3.42 2.74 2.26 4.40
vp9_loop_filter_v_16_16_10bpp_neon: 2.86 2.44 1.93 3.88
The speedup vs C code measured in checkasm is around 1.1-4x.
These numbers are quite inconclusive though, since the checkasm test
runs multiple filterings on top of each other, so later rounds might
end up with different codepaths (different decisions on which filter
to apply, based on input pixel differences).
Based on START_TIMER/STOP_TIMER wrapping around a few individual
functions, the speedup vs C code is around 2-4x.
Signed-off-by: Martin Storsjö <martin@martin.st>
This work is sponsored by, and copyright, Google.
This is structured similarly to the 8 bit version. In the 8 bit
version, the coefficients are 16 bits, and intermediates are 32 bits.
Here, the coefficients are 32 bit. For the 4x4 transforms for 10 bit
content, the intermediates also fit in 32 bits, but for all other
transforms (4x4 for 12 bit content, and 8x8 and larger for both 10
and 12 bit) the intermediates are 64 bit.
For the existing 8 bit case, the 8x8 transform fit all coefficients in
registers; for 10/12 bit, when the coefficients are 32 bit, the 8x8
transform also has to be done in slices of 4 pixels (just as 16x16 and
32x32 for 8 bit).
The slice width also shrinks from 4 elements to 2 elements in parallel
for the 16x16 and 32x32 cases.
The 16 bit coefficients from idct_coeffs and similar tables also need
to be lenghtened to 32 bit in order to be used in multiplication with
vectors with 32 bit elements. This leads to the fixed coefficient
vectors needing more space, leading to more cases where they have to
be reloaded within the transform (in iadst16).
This technically would need testing in checkasm for subpartitions
in increments of 2, but that slows down normal checkasm runs
excessively.
Examples of relative speedup compared to the C version, from checkasm:
Cortex A7 A8 A9 A53
vp9_inv_adst_adst_4x4_sub4_add_10_neon: 4.83 11.36 5.22 6.77
vp9_inv_adst_adst_8x8_sub8_add_10_neon: 4.12 7.60 4.06 4.84
vp9_inv_adst_adst_16x16_sub16_add_10_neon: 3.93 8.16 4.52 5.35
vp9_inv_dct_dct_4x4_sub1_add_10_neon: 1.36 2.57 1.41 1.61
vp9_inv_dct_dct_4x4_sub4_add_10_neon: 4.24 8.66 5.06 5.81
vp9_inv_dct_dct_8x8_sub1_add_10_neon: 2.63 4.18 1.68 2.87
vp9_inv_dct_dct_8x8_sub4_add_10_neon: 4.52 9.47 4.24 5.39
vp9_inv_dct_dct_8x8_sub8_add_10_neon: 3.45 7.34 3.45 4.30
vp9_inv_dct_dct_16x16_sub1_add_10_neon: 3.56 6.21 2.47 4.32
vp9_inv_dct_dct_16x16_sub2_add_10_neon: 5.68 12.73 5.28 7.07
vp9_inv_dct_dct_16x16_sub8_add_10_neon: 4.42 9.28 4.24 5.45
vp9_inv_dct_dct_16x16_sub16_add_10_neon: 3.41 7.29 3.35 4.19
vp9_inv_dct_dct_32x32_sub1_add_10_neon: 4.52 8.35 3.83 6.40
vp9_inv_dct_dct_32x32_sub2_add_10_neon: 5.86 13.19 6.14 7.04
vp9_inv_dct_dct_32x32_sub16_add_10_neon: 4.29 8.11 4.59 5.06
vp9_inv_dct_dct_32x32_sub32_add_10_neon: 3.31 5.70 3.56 3.84
vp9_inv_wht_wht_4x4_sub4_add_10_neon: 1.89 2.80 1.82 1.97
The speedup compared to the C functions is around 1.3 to 7x for the
full transforms, even higher for the smaller subpartitions.
Signed-off-by: Martin Storsjö <martin@martin.st>
This work is sponsored by, and copyright, Google.
The plain pixel put/copy functions are used from the 8 bit version,
for the double size (e.g. put16 uses ff_vp9_copy32_neon), and a new
copy128 is added.
Compared with the 8 bit version, the filters can no longer use the
trick to accumulate in 16 bit with only saturation at the end, but now
the accumulators need to be 32 bit. This avoids the need to keep track
of which filter index is the largest though, reducing the size of the
executable code for these filters.
For the horizontal filters, we only do 4 or 8 pixels wide in parallel
(while doing two rows at a time), since we don't have enough register
space to filter 16 pixels wide.
For the vertical filters, we still do 4 and 8 pixels in parallel just
as in the 8 bit case, but we need to store the output after every 2
rows instead of after every 4 rows.
Examples of relative speedup compared to the C version, from checkasm:
Cortex A7 A8 A9 A53
vp9_avg4_10bpp_neon: 2.25 2.44 3.05 2.16
vp9_avg8_10bpp_neon: 3.66 8.48 3.86 3.50
vp9_avg16_10bpp_neon: 3.39 8.26 3.37 2.72
vp9_avg32_10bpp_neon: 4.03 10.20 4.07 3.42
vp9_avg64_10bpp_neon: 4.15 10.01 4.13 3.70
vp9_avg_8tap_smooth_4h_10bpp_neon: 3.38 6.22 3.41 4.75
vp9_avg_8tap_smooth_4hv_10bpp_neon: 3.89 6.39 4.30 5.32
vp9_avg_8tap_smooth_4v_10bpp_neon: 5.32 9.73 6.34 7.31
vp9_avg_8tap_smooth_8h_10bpp_neon: 4.45 9.40 4.68 6.87
vp9_avg_8tap_smooth_8hv_10bpp_neon: 4.64 8.91 5.44 6.47
vp9_avg_8tap_smooth_8v_10bpp_neon: 6.44 13.42 8.68 8.79
vp9_avg_8tap_smooth_64h_10bpp_neon: 4.66 9.02 4.84 7.71
vp9_avg_8tap_smooth_64hv_10bpp_neon: 4.61 9.14 4.92 7.10
vp9_avg_8tap_smooth_64v_10bpp_neon: 6.90 14.13 9.57 10.41
vp9_put4_10bpp_neon: 1.33 1.46 2.09 1.33
vp9_put8_10bpp_neon: 1.57 3.42 1.83 1.84
vp9_put16_10bpp_neon: 1.55 4.78 2.17 1.89
vp9_put32_10bpp_neon: 2.06 5.35 2.14 2.30
vp9_put64_10bpp_neon: 3.00 2.41 1.95 1.66
vp9_put_8tap_smooth_4h_10bpp_neon: 3.19 5.81 3.31 4.63
vp9_put_8tap_smooth_4hv_10bpp_neon: 3.86 6.22 4.32 5.21
vp9_put_8tap_smooth_4v_10bpp_neon: 5.40 9.77 6.08 7.21
vp9_put_8tap_smooth_8h_10bpp_neon: 4.22 8.41 4.46 6.63
vp9_put_8tap_smooth_8hv_10bpp_neon: 4.56 8.51 5.39 6.25
vp9_put_8tap_smooth_8v_10bpp_neon: 6.60 12.43 8.17 8.89
vp9_put_8tap_smooth_64h_10bpp_neon: 4.41 8.59 4.54 7.49
vp9_put_8tap_smooth_64hv_10bpp_neon: 4.43 8.58 5.34 6.63
vp9_put_8tap_smooth_64v_10bpp_neon: 7.26 13.92 9.27 10.92
For the larger 8tap filters, the speedup vs C code is around 4-14x.
Signed-off-by: Martin Storsjö <martin@martin.st>
This work is sponsored by, and copyright, Google.
This is more in line with how it will be extended for more bitdepths.
Signed-off-by: Martin Storsjö <martin@martin.st>
This treats the case of no slices like no frames which it basically is.
The field is added to the context as other nal related fields are also there
and passing the has_slices field per *arguments is ugly and not consistent
Found-by: ubitux
Approved-by: ubitux
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
CUVID on GeForce GT 730 and GeForce GTX 1060 does not report any error when
decoding 8K h264 packets. However, it does return an error during
cuvidCreateDecoder call if the indicated video resolution is not
supported.
Given that stream resolution is typically known as a result of probing
it is better to use this information during avcodec_open2 call to fail
immediately, rather than proceeding to decode and never receiving any
frames from the decoder nor receiving any indication of decode failure.
Signed-off-by: Timo Rothenpieler <timo@rothenpieler.org>
This makes the code 7 times faster with the testcase from libfuzzer
and should reduce the amount of timeouts we hit in automated fuzzing.
(for example 438/fuzz-2-ffmpeg_VIDEO_AV_CODEC_ID_RV40_fuzzer)
The code is also faster with more realistic input though the difference
is small here as that is far from the worst cases the fuzzers pick out
Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/targets/ffmpeg
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
use av_lfg_init_from_data() to seed AC-3 dithering from the AC-3 frame
data to make it consistent given the same AC-3 frame, if option is set.
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
Raises max channels to 6 (for non joint-stereo only),
there is no difference decoding 1 or N discrete channels.
Fixes trac issue #5840
Signed-off-by: bnnm <bananaman255@gmail.com>
Andreas Cadhalpun
Michael Niedermayer
Clément Bœsch
Carl Eugen Hoyos
Clément Bœsch
Matthieu Bouron
Paul B Mahol
Martin Storsjö
Pavel Koshevoy
Jonathan Campbell
Mark Thompson
bnnm
Daniil Cherednik
Timo Rothenpieler
Aleksandr Slobodeniuk