For this case, with 8 inputs but only changing 4 of them, we can fit
all 16 input pixels into a q register, and still have enough temporary
registers for doing the loop filter.

The wd=8 filters would require too many temporary registers for
processing all 16 pixels at once though.

Before:                          Cortex A7      A8     A9     A53
vp9_loop_filter_mix2_v_44_16_neon:   289.7   256.2  237.5   181.2
After:
vp9_loop_filter_mix2_v_44_16_neon:   221.2   150.5  177.7   138.0

Signed-off-by: Martin Storsjö <martin@martin.st>

This work is sponsored by, and copyright, Google.

The implementation tries to have smart handling of cases
where no pixels need the full filtering for the 8/16 width
filters, skipping both calculation and writeback of the
unmodified pixels in those cases. The actual effect of this
is hard to test with checkasm though, since it tests the
full filtering, and the benefit depends on how many filtered
blocks use the shortcut.

Examples of relative speedup compared to the C version, from checkasm:
                          Cortex       A7     A8     A9    A53
vp9_loop_filter_h_4_8_neon:          2.72   2.68   1.78   3.15
vp9_loop_filter_h_8_8_neon:          2.36   2.38   1.70   2.91
vp9_loop_filter_h_16_8_neon:         1.80   1.89   1.45   2.01
vp9_loop_filter_h_16_16_neon:        2.81   2.78   2.18   3.16
vp9_loop_filter_mix2_h_44_16_neon:   2.65   2.67   1.93   3.05
vp9_loop_filter_mix2_h_48_16_neon:   2.46   2.38   1.81   2.85
vp9_loop_filter_mix2_h_84_16_neon:   2.50   2.41   1.73   2.85
vp9_loop_filter_mix2_h_88_16_neon:   2.77   2.66   1.96   3.23
vp9_loop_filter_mix2_v_44_16_neon:   4.28   4.46   3.22   5.70
vp9_loop_filter_mix2_v_48_16_neon:   3.92   4.00   3.03   5.19
vp9_loop_filter_mix2_v_84_16_neon:   3.97   4.31   2.98   5.33
vp9_loop_filter_mix2_v_88_16_neon:   3.91   4.19   3.06   5.18
vp9_loop_filter_v_4_8_neon:          4.53   4.47   3.31   6.05
vp9_loop_filter_v_8_8_neon:          3.58   3.99   2.92   5.17
vp9_loop_filter_v_16_8_neon:         3.40   3.50   2.81   4.68
vp9_loop_filter_v_16_16_neon:        4.66   4.41   3.74   6.02

The speedup vs C code is around 2-6x. The 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). Disabling the early-exit in the asm
doesn't give a fair comparison either though, since the C code
only does the necessary calcuations for each row.

Based on START_TIMER/STOP_TIMER wrapping around a few individual
functions, the speedup vs C code is around 4-9x.

This is pretty similar in runtime to the corresponding routines
in libvpx. (This is comparing vpx_lpf_vertical_16_neon,
vpx_lpf_horizontal_edge_8_neon and vpx_lpf_horizontal_edge_16_neon
to vp9_loop_filter_h_16_8_neon, vp9_loop_filter_v_16_8_neon
and vp9_loop_filter_v_16_16_neon - note that the naming of horizonal
and vertical is flipped between the libraries.)

In order to have stable, comparable numbers, the early exits in both
asm versions were disabled, forcing the full filtering codepath.

                           Cortex           A7      A8      A9     A53
vp9_loop_filter_h_16_8_neon:             597.2   472.0   482.4   415.0
libvpx vpx_lpf_vertical_16_neon:         626.0   464.5   470.7   445.0
vp9_loop_filter_v_16_8_neon:             500.2   422.5   429.7   295.0
libvpx vpx_lpf_horizontal_edge_8_neon:   586.5   414.5   415.6   383.2
vp9_loop_filter_v_16_16_neon:            905.0   784.7   791.5   546.0
libvpx vpx_lpf_horizontal_edge_16_neon: 1060.2   751.7   743.5   685.2

Our version is consistently faster on on A7 and A53, marginally slower on
A8, and sometimes faster, sometimes slower on A9 (marginally slower in all
three tests in this particular test run).

Signed-off-by: Martin Storsjö <martin@martin.st>

This work is sponsored by, and copyright, Google.

For the transforms up to 8x8, we can fit all the data (including
temporaries) in registers and just do a straightforward transform
of all the data. For 16x16, we do a transform of 4x16 pixels in
4 slices, using a temporary buffer. For 32x32, we transform 4x32
pixels at a time, in two steps of 4x16 pixels each.

Examples of relative speedup compared to the C version, from checkasm:
                         Cortex       A7     A8     A9    A53
vp9_inv_adst_adst_4x4_add_neon:     3.39   5.83   4.17   4.01
vp9_inv_adst_adst_8x8_add_neon:     3.79   4.86   4.23   3.98
vp9_inv_adst_adst_16x16_add_neon:   3.33   4.36   4.11   4.16
vp9_inv_dct_dct_4x4_add_neon:       4.06   6.16   4.59   4.46
vp9_inv_dct_dct_8x8_add_neon:       4.61   6.01   4.98   4.86
vp9_inv_dct_dct_16x16_add_neon:     3.35   3.44   3.36   3.79
vp9_inv_dct_dct_32x32_add_neon:     3.89   3.50   3.79   4.42
vp9_inv_wht_wht_4x4_add_neon:       3.22   5.13   3.53   3.77

Thus, the speedup vs C code is around 3-6x.

This is mostly marginally faster than the corresponding routines
in libvpx on most cores, tested with their 32x32 idct (compared to
vpx_idct32x32_1024_add_neon). These numbers are slightly in libvpx's
favour since their version doesn't clear the input buffer like ours
do (although the effect of that on the total runtime probably is
negligible.)

                           Cortex       A7       A8       A9      A53
vp9_inv_dct_dct_32x32_add_neon:    18436.8  16874.1  14235.1  11988.9
libvpx vpx_idct32x32_1024_add_neon 20789.0  13344.3  15049.9  13030.5

Only on the Cortex A8, the libvpx function is faster. On the other cores,
ours is slightly faster even though ours has got source block clearing
integrated.

Signed-off-by: Martin Storsjö <martin@martin.st>

This work is sponsored by, and copyright, Google.

The speedup for the large horizontal filters is surprisingly
big on A7 and A53, while there's a minor slowdown (almost within
measurement noise) on A8 and A9.

                            Cortex    A7        A8        A9       A53
orig:
vp9_put_8tap_smooth_64h_neon:    20270.0   14447.3   19723.9   10910.9
new:
vp9_put_8tap_smooth_64h_neon:    20165.8   14466.5   19730.2   10668.8

Signed-off-by: Martin Storsjö <martin@martin.st>

This work is sponsored by, and copyright, Google.

The filter coefficients are signed values, where the product of the
multiplication with one individual filter coefficient doesn't
overflow a 16 bit signed value (the largest filter coefficient is
127). But when the products are accumulated, the resulting sum can
overflow the 16 bit signed range. Instead of accumulating in 32 bit,
we accumulate the largest product (either index 3 or 4) last with a
saturated addition.

(The VP8 MC asm does something similar, but slightly simpler, by
accumulating each half of the filter separately. In the VP9 MC
filters, each half of the filter can also overflow though, so the
largest component has to be handled individually.)

Examples of relative speedup compared to the C version, from checkasm:
                       Cortex      A7     A8     A9    A53
vp9_avg4_neon:                   1.71   1.15   1.42   1.49
vp9_avg8_neon:                   2.51   3.63   3.14   2.58
vp9_avg16_neon:                  2.95   6.76   3.01   2.84
vp9_avg32_neon:                  3.29   6.64   2.85   3.00
vp9_avg64_neon:                  3.47   6.67   3.14   2.80
vp9_avg_8tap_smooth_4h_neon:     3.22   4.73   2.76   4.67
vp9_avg_8tap_smooth_4hv_neon:    3.67   4.76   3.28   4.71
vp9_avg_8tap_smooth_4v_neon:     5.52   7.60   4.60   6.31
vp9_avg_8tap_smooth_8h_neon:     6.22   9.04   5.12   9.32
vp9_avg_8tap_smooth_8hv_neon:    6.38   8.21   5.72   8.17
vp9_avg_8tap_smooth_8v_neon:     9.22  12.66   8.15  11.10
vp9_avg_8tap_smooth_64h_neon:    7.02  10.23   5.54  11.58
vp9_avg_8tap_smooth_64hv_neon:   6.76   9.46   5.93   9.40
vp9_avg_8tap_smooth_64v_neon:   10.76  14.13   9.46  13.37
vp9_put4_neon:                   1.11   1.47   1.00   1.21
vp9_put8_neon:                   1.23   2.17   1.94   1.48
vp9_put16_neon:                  1.63   4.02   1.73   1.97
vp9_put32_neon:                  1.56   4.92   2.00   1.96
vp9_put64_neon:                  2.10   5.28   2.03   2.35
vp9_put_8tap_smooth_4h_neon:     3.11   4.35   2.63   4.35
vp9_put_8tap_smooth_4hv_neon:    3.67   4.69   3.25   4.71
vp9_put_8tap_smooth_4v_neon:     5.45   7.27   4.49   6.52
vp9_put_8tap_smooth_8h_neon:     5.97   8.18   4.81   8.56
vp9_put_8tap_smooth_8hv_neon:    6.39   7.90   5.64   8.15
vp9_put_8tap_smooth_8v_neon:     9.03  11.84   8.07  11.51
vp9_put_8tap_smooth_64h_neon:    6.78   9.48   4.88  10.89
vp9_put_8tap_smooth_64hv_neon:   6.99   8.87   5.94   9.56
vp9_put_8tap_smooth_64v_neon:   10.69  13.30   9.43  14.34

For the larger 8tap filters, the speedup vs C code is around 5-14x.

This is significantly faster than libvpx's implementation of the same
functions, at least when comparing the put_8tap_smooth_64 functions
(compared to vpx_convolve8_horiz_neon and vpx_convolve8_vert_neon from
libvpx).

Absolute runtimes from checkasm:
                          Cortex      A7        A8        A9       A53
vp9_put_8tap_smooth_64h_neon:    20150.3   14489.4   19733.6   10863.7
libvpx vpx_convolve8_horiz_neon: 52623.3   19736.4   21907.7   25027.7

vp9_put_8tap_smooth_64v_neon:    14455.0   12303.9   13746.4    9628.9
libvpx vpx_convolve8_vert_neon:  42090.0   17706.2   17659.9   16941.2

Thus, on the A9, the horizontal filter is only marginally faster than
libvpx, while our version is significantly faster on the other cores,
and the vertical filter is significantly faster on all cores. The
difference is especially large on the A7.

The libvpx implementation does the accumulation in 32 bit, which
probably explains most of the differences.

Signed-off-by: Martin Storsjö <martin@martin.st>