我执行双线性插值在紧密循环,并试图与SSE优化它,但我从它那里得到零加速。
下面是代码,非SIMD版本使用其可被定义为一个简单的矢量的结构struct Vec3f { float x, y, z; }
struct Vec3f { float x, y, z; }
与实施乘法和加法运算符:
#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, s11};
__declspec(align(16)) float ms12[4] = {1.0, s12, s12, s12};
__declspec(align(16)) float ms22[4] = {1.0, s22, s22, s22};
__declspec(align(16)) float ms21[4] = {1.0, s21, 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
重新整理汇编代码重用寄存器(结束了只有三个XMM寄存器)没有给任何影响。 我一直在使用内部函数也尝试:
// 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, s11, s11);
__m128 ms12 = _mm_set_ps(1.f, s12, s12, s12);
__m128 ms22 = _mm_set_ps(1.f, s22, s22, s22);
__m128 ms21 = _mm_set_ps(1.f, s21, s21, 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);
而且无济于事。 难道我失去了一些东西,或者是不可能在这里获得任何额外的速度?