字节我有32 bpp图像。我需要在不同的16位向量中交错R G B颜色通道我正在使用以下代码来执行此操作(how to deinterleave image channel in SSE)
// deinterleave chaneel R, G, B ,A in 16 bits vectors
{
__m128i vrgba = _mm_loadu_si128((__m128i *)(pSrc));
__m128i vr1 = _mm_and_si128(vrgba, _mm_set1_epi32(0xff));
__m128i vg1 = _mm_and_si128(_mm_srli_epi32(vrgba, 8), _mm_set1_epi32(0xff));
__m128i vb1 = _mm_and_si128(_mm_srli_epi32(vrgba, 16), _mm_set1_epi32(0xff));
__m128i va1 = _mm_srli_epi32(vrgba, 24);
vrgba = _mm_loadu_si128((__m128i *)(pSrc + 4)); // since pSrc is uint32_t type
__m128i vr2 = _mm_and_si128(vrgba, _mm_set1_epi32(0xff));
__m128i vg2 = _mm_and_si128(_mm_srli_epi32(vrgba, 8), _mm_set1_epi32(0xff));
__m128i vb2 = _mm_and_si128(_mm_srli_epi32(vrgba, 16), _mm_set1_epi32(0xff));
__m128i va2 = _mm_srli_epi32(vrgba, 24);
vr = _mm_packs_epi32(vr1, vr2);
vg = _mm_packs_epi32(vg1, vg2);
vb = _mm_packs_epi32(vb1, vb2);
va = _mm_packs_epi32(va1, va2);
}
我们可以提高效率吗?下面是高斯没有去交织信道的代码。我发现它非常低效
static inline void ConvertTo16Bits(__m128i& v1, __m128i& v2, const __m128i& v0)
{
__m128i const zero = _mm_setzero_si128();
v1 = _mm_unpacklo_epi8(v0, zero);
v2 = _mm_unpackhi_epi8(v0, zero);
}
static inline void mul32bits(__m128i &vh, __m128i &vl, // output - 2x4xint32_t
const __m128i& v0, const __m128i& v1) // input - 2x8xint16_t
{
const __m128i vhi = _mm_mulhi_epu16(v0, v1);
const __m128i vlo = _mm_mullo_epi16(v0, v1);
vh = _mm_unpacklo_epi16(vlo, vhi);
vl = _mm_unpackhi_epi16(vlo, vhi);
}
struct Pixel
{
unsigned char r;
unsigned char g;
unsigned char b;
unsigned char a;
};
void computePixelvalue(unsigned int * pixelArray, int count, unsigned short * gaussArray, Pixel& out)
{
__m128i sumRGBA;
sumRGBA = _mm_set1_epi32(0);
unsigned int countMod4 = count % 4;
unsigned int b, g, r, a;
constexpr int shuffle = _MM_SHUFFLE(3, 1, 0, 0);
while (count >= 4)
{
__m128i vrgba = _mm_loadu_si128((__m128i *)(pixelArray));
__m128i rgba12, rgba34;
ConvertTo16Bits(rgba12, rgba34, vrgba);
unsigned short s1 = *gaussArray++;
unsigned short s2 = *gaussArray++;
__m128i shift8 = _mm_set1_epi16(s1);
__m128i shift16 = _mm_set1_epi16(s2);
__m128i gaussVector = _mm_shuffle_epi32(_mm_unpacklo_epi32(shift8, shift16), shuffle);
__m128i multl, multh;
mul32bits(multl, multh, rgba12, gaussVector);
sumRGBA = _mm_add_epi32(sumRGBA, multl);
sumRGBA = _mm_add_epi32(sumRGBA, multh);
s1 = *gaussArray++;
s2 = *gaussArray++;
shift8 = _mm_set1_epi16(s1);
shift16 = _mm_set1_epi16(s2);
gaussVector = _mm_shuffle_epi32(_mm_unpacklo_epi32(shift8, shift16), shuffle);
mul32bits(multl, multh, rgba34, gaussVector);
sumRGBA = _mm_add_epi32(sumRGBA, multl);
sumRGBA = _mm_add_epi32(sumRGBA, multh);
count = count - 4;
pixelArray = pixelArray + 4;
}
r = sumRGBA.m128i_u32[0];
g = sumRGBA.m128i_u32[1];
b = sumRGBA.m128i_u32[2];
a = sumRGBA.m128i_u32[3];
while (countMod4)
{
auto pixelArrayByte = reinterpret_cast<unsigned char*>(pixelArray);
unsigned short k = static_cast<unsigned short>(*gaussArray++);
r += *pixelArrayByte++ * k;
g += *pixelArrayByte++ * k;
b += *pixelArrayByte++ * k;
a += *pixelArrayByte++ * k;
countMod4--;
}
out.r = static_cast<unsigned char>(r >> 15);
out.g = static_cast<unsigned char>(g >> 15);
out.b = static_cast<unsigned char>(b >> 15);
out.a = static_cast<unsigned char>(a >> 15);
}
答案 0 :(得分:3)
pshufb
的{{1}}个向量转换为{ a b g r ... }
的向量(每个源向量一个pshufb)。
两个混洗的源向量之间的 { a a a a b b b b g g g g r r r r }
得到punpckldq
。 { g2g2g2g2 g1g1g1g1 r2r2r2r2 r1r1r1r1 }
低半部分,用零解包高半部分,得到只有g和r的向量。
同样地,pmovzxbw
获得punpckhdq
相同的两个源向量。
所以每4个输入向量(产生8个输出向量),那就是:
总共10条ALU指令,不包括任何复制,以避免破坏仍然需要的数据。
这与掩码/移位/包方法所需的32条指令相比非常好。 (并且没有AVX,这将涉及相当多的复制,以4种不同的方式屏蔽相同的向量。)这些指令中的8个是{ a2a2a2a2 a1a1a1a1 b2b2b2b2 b1b1b1b1 }
随机指令,因此它在shuffle端口上的压力稍微小一点,以换取更多的总指示。
Haswell只能在一个执行端口上进行随机播放,这个端口与位移不同。 (并且pack
可以在三个向量执行端口中的任何一个上运行)。我非常有信心10次洗牌方式将获得相当大的优势,因为更多的计算可以与之重叠。
_mm_and
可能作为来自两个源向量的shuffle有用,但它具有32位粒度,所以我看不到它的用途。在Intel SnB系列和AMD Bulldozer系列中,在整数向量指令之间使用它不会受到任何惩罚。
另一个想法:
shufps
将__m128i rgba1 = _mm_loadu_si128((__m128i *)(pSrc)); // { a1.4 b1.4 g1.4 r1.4 ... a1.1 b1.1 g1.1 r1.1 }
__m128i rgba2 = _mm_loadu_si128((__m128i *)(pSrc+4)); // { a2.4 b2.4 ... g2.1 r2.1 }
__m128i rg1 = _mm_and_si128 (rgba1, _mm_set1_epi32(0xffff));
__m128i rg2 = _mm_slli_epi32(rgba2, 16);
__m128i rg_interleaved = _mm_or_si128(rg2, rg1); // { g2.4 r2.4 g1.4 r1.4 ... g2.1 r2.1 g1.1 r1.1 }
分隔为零扩展的16位r和g向量与另一个rg_interleaved
和_mm_and_si128
。