这是代码,非SIMD版本使用简单的向量结构,可以定义为struct Vec3f {float x,y,z;使用已实现的乘法和加法运算符：

#ifdef USE_SIMD
    const Color c11 = pixelCache[y1 * size.x + x1];
    const Color c12 = pixelCache[y2 * size.x + x1];
    const Color c22 = pixelCache[y2 * size.x + x2];
    const Color c21 = pixelCache[y1 * size.x + x2];
 
    __declspec(align(16)) float mc11[4] = { 1.0,c11.GetB(),c11.GetG(),c11.GetR() };
    __declspec(align(16)) float mc12[4] = { 1.0,c12.GetB(),c12.GetG(),c12.GetR() };
    __declspec(align(16)) float mc22[4] = { 1.0,c22.GetB(),c22.GetG(),c22.GetR() };
    __declspec(align(16)) float mc21[4] = { 1.0,c21.GetB(),c21.GetG(),c21.GetR() };
 
    // scalars in vector form for SSE
    const float s11 = (x2-x)*(y2-y);
    const float s12 = (x2-x)*(y-y1);
    const float s22 = (x-x1)*(y-y1);
    const float s21 = (x-x1)*(y2-y);
 
    __declspec(align(16)) float ms11[4] = {1.0,s11,s11};
    __declspec(align(16)) float ms12[4] = {1.0,s12,s12};
    __declspec(align(16)) float ms22[4] = {1.0,s22,s22};
    __declspec(align(16)) float ms21[4] = {1.0,s21,s21};
 
    __asm {
        movaps xmm0,mc11
        movaps xmm1,mc12
        movaps xmm2,mc22
        movaps xmm3,mc21
 
        movaps xmm4,ms11
        movaps xmm5,ms12
        movaps xmm6,ms22
        movaps xmm7,ms21
 
        mulps xmm0,xmm4
        mulps xmm1,xmm5
        mulps xmm2,xmm6
        mulps xmm3,xmm7
 
        addps xmm0,xmm1
        addps xmm0,xmm2
        addps xmm0,xmm3
 
        movaps mc11,xmm0
    }
#else
    const Vec3f c11 = toFloat(pixelCache[y1 * size.x + x1]);
    const Vec3f c12 = toFloat(pixelCache[y2 * size.x + x1]);
    const Vec3f c22 = toFloat(pixelCache[y2 * size.x + x2]);
    const Vec3f c21 = toFloat(pixelCache[y1 * size.x + x2]);
 
    const Vec3f colour =
            c11*(x2-x)*(y2-y) +
            c21*(x-x1)*(y2-y) +
            c12*(x2-x)*(y-y1) +
            c22*(x-x1)*(y-y1);
#endif

重新排列asm代码以重用寄存器(最后只有三个xmm寄存器)并没有产生任何影响.我也试过使用内在函数：

// perform bilinear interpolation
const Vec3f c11 = toFloat(pixelCache[y1 * size.x + x1]);
const Vec3f c12 = toFloat(pixelCache[y2 * size.x + x1]);
const Vec3f c22 = toFloat(pixelCache[y2 * size.x + x2]);
const Vec3f c21 = toFloat(pixelCache[y1 * size.x + x2]);
 
// scalars in vector form for SSE
const float s11 = (x2-x)*(y2-y);
const float s12 = (x2-x)*(y-y1);
const float s22 = (x-x1)*(y-y1);
const float s21 = (x-x1)*(y2-y);
 
__m128 mc11 = _mm_set_ps(1.f,c11.b,c11.g,c11.r);
__m128 mc12 = _mm_set_ps(1.f,c12.b,c12.g,c12.r);
__m128 mc22 = _mm_set_ps(1.f,c22.b,c22.g,c22.r);
__m128 mc21 = _mm_set_ps(1.f,c21.b,c21.g,c21.r);
 
__m128 ms11 = _mm_set_ps(1.f,s11);
__m128 ms12 = _mm_set_ps(1.f,s12);
__m128 ms22 = _mm_set_ps(1.f,s22);
__m128 ms21 = _mm_set_ps(1.f,s21);
 
mc11 = _mm_mul_ps(mc11,ms11);
mc12 = _mm_mul_ps(mc12,ms12);
mc22 = _mm_mul_ps(mc22,ms22);
mc21 = _mm_mul_ps(mc21,ms21);
 
mc11 = _mm_add_ps(mc11,mc12);
mc11 = _mm_add_ps(mc11,mc22);
mc11 = _mm_add_ps(mc11,mc21);
 
Vec3f colour;
_mm_storeu_ps(colour.array,mc11);

并无济于事.我错过了什么,或者在这里不可能获得任何额外的速度？