Question

我正在尝试从YCbCr到BGRA执行图像颜色转换（不要问A位，这么头疼）。

无论如何，这需要尽可能快地执行，所以我使用编译器内在函数来编写它以利用SSE2。这是我第一次进入SIMD土地，我基本上是一个初学者，所以我确信我的工作效率很低。

我进行实际颜色转换的算术代码变得特别慢，英特尔的VTune显示它是一个重要的瓶颈。

那么，我可以用任何方式加快以下代码的速度吗？它以32位，一次4个像素完成。我最初尝试以8位，一次16个像素（如上部循环），但计算导致整数溢出和转换损坏。整个过程，包括英特尔jpeg解码，单个全高清领域需要大约14毫秒。如果我能把它降到至少12毫秒，理想情况下是10毫秒，那就太棒了。

感谢任何帮助或提示。谢谢！

const __m128i s128_8    = _mm_set1_epi8((char)128);


const int nNumPixels = roi.width * roi.height;

for (int i=0; i<nNumPixels; i+=32)
{
    // Go ahead and prefetch our packed UV Data.
    // As long as the load remains directly next, this saves us time.
    _mm_prefetch((const char*)&pSrc8u[2][i],_MM_HINT_T0); 

    // We need to fetch and blit out our k before we write over it with UV data.
    __m128i sK1 = _mm_load_si128((__m128i*)&pSrc8u[2][i]);
    __m128i sK2 = _mm_load_si128((__m128i*)&pSrc8u[2][i+16]);

    // Using the destination buffer temporarily here so we don't need to waste time doing a memory allocation.
    _mm_store_si128 ((__m128i*)&m_pKBuffer[i],      sK1);
    _mm_store_si128 ((__m128i*)&m_pKBuffer[i+16],   sK2);

    // In theory, this prefetch needs to be some cycles ahead of the first read. It isn't, yet it does appear to save us time. Worth investigating.
    _mm_prefetch((const char*)&pSrc8u[1][i],_MM_HINT_T0); 

    __m128i sUVI1 = _mm_load_si128((__m128i*)&pSrc8u[1][i]);
    __m128i sUVI2 = _mm_load_si128((__m128i*)&pSrc8u[1][i+16]);  

    // Subtract the 128 here ahead of our YCbCr -> BGRA conversion so we can go 16 pixels at a time rather than 4.
    sUVI1 = _mm_sub_epi8(sUVI1, s128_8);
    sUVI2 = _mm_sub_epi8(sUVI2, s128_8);

    // Swizzle and double up UV data from interleaved 8x1 byte blocks into planar
    __m128i sU1 = _mm_unpacklo_epi8(sUVI1, sUVI1);
    __m128i sV1 = _mm_unpackhi_epi8(sUVI1, sUVI1);

    __m128i sU2 = _mm_unpacklo_epi8(sUVI2, sUVI2);  
    __m128i sV2 = _mm_unpackhi_epi8(sUVI2, sUVI2);  

    _mm_store_si128((__m128i*)&pSrc8u[1][i],        sU1);
    _mm_store_si128((__m128i*)&pSrc8u[1][i+16],     sU2); 

    _mm_store_si128((__m128i*)&pSrc8u[2][i],        sV1);
    _mm_store_si128((__m128i*)&pSrc8u[2][i+16],     sV2); 
}

const __m128i s16   = _mm_set1_epi32(16);
const __m128i s299  = _mm_set1_epi32(299);
const __m128i s410  = _mm_set1_epi32(410);
const __m128i s518  = _mm_set1_epi32(518);
const __m128i s101  = _mm_set1_epi32(101);
const __m128i s209  = _mm_set1_epi32(209);

Ipp8u* pDstP = pDst8u;
for (int i=0; i<nNumPixels; i+=4, pDstP+=16)
{
    __m128i sK = _mm_set_epi32(m_pKBuffer[i],           m_pKBuffer[i+1],            m_pKBuffer[i+2],            m_pKBuffer[i+3]);

    __m128i sY = _mm_set_epi32(pSrc8u[0][i],            pSrc8u[0][i+1],             pSrc8u[0][i+2],             pSrc8u[0][i+3]);
    __m128i sU = _mm_set_epi32((char)pSrc8u[1][i],      (char)pSrc8u[1][i+1],       (char)pSrc8u[1][i+2],       (char)pSrc8u[1][i+3]);
    __m128i sV = _mm_set_epi32((char)pSrc8u[2][i],      (char)pSrc8u[2][i+1],       (char)pSrc8u[2][i+2],       (char)pSrc8u[2][i+3]);

    // N.b. - Attempted to do the sub 16 in 8 bits similar to the sub 128 for U and V - however doing it here is quicker
    // as the time saved on the arithmetic is less than the time taken by the additional loads/stores needed in the swizzle loop
    sY = _mm_mullo_epi32(_mm_sub_epi32(sY, s16), s299);

    __m128i sR  = _mm_srli_epi32(_mm_add_epi32(sY,_mm_mullo_epi32(s410, sV)), 8);
    __m128i sG  = _mm_srli_epi32(_mm_sub_epi32(_mm_sub_epi32(sY, _mm_mullo_epi32(s101, sU)),_mm_mullo_epi32(s209, sV)), 8);
    __m128i sB  = _mm_srli_epi32(_mm_add_epi32(sY, _mm_mullo_epi32(s518, sU)), 8);

    //Microsoft's YUV Conversion
    //__m128i sC = _mm_sub_epi32(sY, s16);
    //__m128i sD = _mm_sub_epi32(sU, s128);
    //__m128i sE = _mm_sub_epi32(sV, s128);
    //
    //__m128i sR =  _mm_srli_epi32(_mm_add_epi32(_mm_add_epi32(_mm_mullo_epi32(s298, sC), _mm_mullo_epi32(s409, sE)), s128), 8);
    //__m128i sG    = _mm_srli_epi32(_mm_add_epi32(_mm_sub_epi32(_mm_mullo_epi32(s298, sC), _mm_sub_epi32(_mm_mullo_epi32(s100, sD), _mm_mullo_epi32(s208, sE))), s128), 8);
    //__m128i sB    = _mm_srli_epi32(_mm_add_epi32(_mm_add_epi32(_mm_mullo_epi32(s298, sC), _mm_mullo_epi32(s516, sD)), s128), 8);

    __m128i sKGl = _mm_unpacklo_epi32(sK, sG);
    __m128i sKGh = _mm_unpackhi_epi32(sK, sG);

    __m128i sRBl = _mm_unpacklo_epi32(sR, sB);
    __m128i sRBh = _mm_unpackhi_epi32(sR, sB);

    __m128i sKRGB1 = _mm_unpackhi_epi32(sKGh,sRBh);
    __m128i sKRGB2 = _mm_unpacklo_epi32(sKGh,sRBh);
    __m128i sKRGB3 = _mm_unpackhi_epi32(sKGl,sRBl);
    __m128i sKRGB4 = _mm_unpacklo_epi32(sKGl,sRBl);

    __m128i p1 = _mm_packus_epi16(sKRGB1, sKRGB2);
    __m128i p2 = _mm_packus_epi16(sKRGB3, sKRGB4);

    __m128i po = _mm_packus_epi16(p1, p2);

    _mm_store_si128((__m128i*)pDstP, po);
}

Answer 1

这里的带宽有限，因为相对于加载和存储的数量，计算量非常小。

一个建议：摆脱_mm_prefetch内在函数 - 它们几乎肯定没有帮助，甚至可能阻碍更近期CPU的运行（已经在自动预取方面表现相当不错）。

另一个值得关注的领域：

__m128i sK = _mm_set_epi32(m_pKBuffer[i],           m_pKBuffer[i+1],            m_pKBuffer[i+2],            m_pKBuffer[i+3]);
__m128i sY = _mm_set_epi32(pSrc8u[0][i],            pSrc8u[0][i+1],             pSrc8u[0][i+2],             pSrc8u[0][i+3]);
__m128i sU = _mm_set_epi32((char)pSrc8u[1][i],      (char)pSrc8u[1][i+1],       (char)pSrc8u[1][i+2],       (char)pSrc8u[1][i+3]);
__m128i sV = _mm_set_epi32((char)pSrc8u[2][i],      (char)pSrc8u[2][i+1],       (char)pSrc8u[2][i+2],       (char)pSrc8u[2][i+3]);

这会产生批次不必要的指示 - 您应该在此使用_mm_load_xxx和_mm_unpackxx_xxx。它将看起来像更多的代码，但效率会更高。你应该每循环处理16个像素，而不是4个 - 这样你就可以加载一个8位值的向量，然后解压缩，根据需要将每组4个值作为32位整数的向量。< / p>

加快一些SSE2内在函数的颜色转换

1 个答案: