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Optimize SSE4.1 version of SAD

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Make it use the same vblend trick as AVX2. Interestingly, on my test
setup this seems to be faster than the same code using 256-bit AVX
vectors.
This commit is contained in:
Pauli Oikkonen 2019-01-07 19:28:10 +02:00
parent 887d7700a8
commit b2176bf72a
1 changed files with 24 additions and 45 deletions
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69
src/strategies/sse41/picture-sse41.c
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@ -32,59 +32,38 @@ unsigned kvz_reg_sad_sse41(const kvz_pixel * const data1, const kvz_pixel * cons
const int width, const int height, const unsigned stride1, const unsigned stride2) const int width, const int height, const unsigned stride1, const unsigned stride2)
{ {
int y, x; int y, x;
unsigned sad = 0; __m128i sse_inc = _mm_setzero_si128();
__m128i sse_inc = _mm_setzero_si128 ();
long long int sse_inc_array[2];
// Bytes in block in 128-bit blocks per each scanline, and remainder
const int largeblock_bytes = width & ~15;
const int residual_bytes = width & 15;
const __m128i rds = _mm_set1_epi8 (residual_bytes);
const __m128i ns = _mm_setr_epi8 (0, 1, 2, 3, 4, 5, 6, 7,
8, 9, 10, 11, 12, 13, 14, 15);
const __m128i rdmask = _mm_cmpgt_epi8(rds, ns);
for (y = 0; y < height; ++y) { for (y = 0; y < height; ++y) {
for (x = 0; x <= width-16; x+=16) { for (x = 0; x < largeblock_bytes; x += 16) {
const __m128i a = _mm_loadu_si128((__m128i const*) &data1[y * stride1 + x]); __m128i a = _mm_loadu_si128((__m128i const*) &data1[y * stride1 + x]);
const __m128i b = _mm_loadu_si128((__m128i const*) &data2[y * stride2 + x]); __m128i b = _mm_loadu_si128((__m128i const*) &data2[y * stride2 + x]);
sse_inc = _mm_add_epi32(sse_inc, _mm_sad_epu8(a,b)); __m128i curr_sads = _mm_sad_epu8(a, b);
sse_inc = _mm_add_epi32(sse_inc, curr_sads);
} }
{ if (residual_bytes) {
const __m128i a = _mm_loadu_si128((__m128i const*) &data1[y * stride1 + x]); __m128i a = _mm_loadu_si128((__m128i const*) &data1[y * stride1 + x]);
const __m128i b = _mm_loadu_si128((__m128i const*) &data2[y * stride2 + x]); __m128i b = _mm_loadu_si128((__m128i const*) &data2[y * stride2 + x]);
switch (((width - (width%2)) - x)/2) {
case 0:
break;
case 1:
sse_inc = _mm_add_epi32(sse_inc, _mm_sad_epu8(a, _mm_blend_epi16(a, b, 0x01)));
break;
case 2:
sse_inc = _mm_add_epi32(sse_inc, _mm_sad_epu8(a, _mm_blend_epi16(a, b, 0x03)));
break;
case 3:
sse_inc = _mm_add_epi32(sse_inc, _mm_sad_epu8(a, _mm_blend_epi16(a, b, 0x07)));
break;
case 4:
sse_inc = _mm_add_epi32(sse_inc, _mm_sad_epu8(a, _mm_blend_epi16(a, b, 0x0f)));
break;
case 5:
sse_inc = _mm_add_epi32(sse_inc, _mm_sad_epu8(a, _mm_blend_epi16(a, b, 0x1f)));
break;
case 6:
sse_inc = _mm_add_epi32(sse_inc, _mm_sad_epu8(a, _mm_blend_epi16(a, b, 0x3f)));
break;
case 7:
sse_inc = _mm_add_epi32(sse_inc, _mm_sad_epu8(a, _mm_blend_epi16(a, b, 0x7f)));
break;
default:
//Should not happen
assert(0);
}
x = (width - (width%2));
}
for (; x < width; ++x) { __m128i b_masked = _mm_blendv_epi8(a, b, rdmask);
sad += abs(data1[y * stride1 + x] - data2[y * stride2 + x]); __m128i curr_sads = _mm_sad_epu8(a, b_masked);
sse_inc = _mm_add_epi32(sse_inc, curr_sads);
} }
} }
_mm_storeu_si128((__m128i*) sse_inc_array, sse_inc); __m128i sse_inc_2 = _mm_shuffle_epi32(sse_inc, _MM_SHUFFLE(1, 0, 3, 2));
sad += sse_inc_array[0] + sse_inc_array[1]; __m128i sad = _mm_add_epi64 (sse_inc, sse_inc_2);
return sad; return _mm_cvtsi128_si32(sad);
} }
#endif //COMPILE_INTEL_SSE41 #endif //COMPILE_INTEL_SSE41