How do I perform 8 x 8 matrix operation using SSE?

问题:

My initial attempt looked like this (supposed we want to multiply)

  __m128 mat[n]; /* rows */
  __m128 vec[n] = {1,1,1,1};
  float outvector[n];
   for (int row=0;row<n;row++) {
       for(int k =3; k < 8; k = k+ 4)
       {
           __m128 mrow = mat[k];
           __m128 v = vec[row];
           __m128 sum = _mm_mul_ps(mrow,v);
           sum= _mm_hadd_ps(sum,sum); /* adds adjacent-two floats */
       }
           _mm_store_ss(&outvector[row],_mm_hadd_ps(sum,sum));
 }

But this clearly doesn't work. How do I approach this?

I should load 4 at a time....

The other question is: if my array is very big (say n = 1000), how can I make it 16-bytes aligned? Is that even possible?

回答1:

OK... I'll use a row-major matrix convention. Each row of [m] requires (2) __m128 elements to yield 8 floats. The 8x1 vector v is a column vector. Since you're using the haddps instruction, I'll assume SSE3 is available. Finding r = [m] * v :

void mul (__m128 r[2], const __m128 m[8][2], const __m128 v[2])
{
    __m128 t0, t1, t2, t3, r0, r1, r2, r3;

    t0 = _mm_mul_ps(m[0][0], v[0]);
    t1 = _mm_mul_ps(m[1][0], v[0]);
    t2 = _mm_mul_ps(m[2][0], v[0]);
    t3 = _mm_mul_ps(m[3][0], v[0]);

    t0 = _mm_hadd_ps(t0, t1);
    t2 = _mm_hadd_ps(t2, t3);
    r0 = _mm_hadd_ps(t0, t2);

    t0 = _mm_mul_ps(m[0][1], v[1]);
    t1 = _mm_mul_ps(m[1][1], v[1]);
    t2 = _mm_mul_ps(m[2][1], v[1]);
    t3 = _mm_mul_ps(m[3][1], v[1]);

    t0 = _mm_hadd_ps(t0, t1);
    t2 = _mm_hadd_ps(t2, t3);
    r1 = _mm_hadd_ps(t0, t2);

    t0 = _mm_mul_ps(m[4][0], v[0]);
    t1 = _mm_mul_ps(m[5][0], v[0]);
    t2 = _mm_mul_ps(m[6][0], v[0]);
    t3 = _mm_mul_ps(m[7][0], v[0]);

    t0 = _mm_hadd_ps(t0, t1);
    t2 = _mm_hadd_ps(t2, t3);
    r2 = _mm_hadd_ps(t0, t2);

    t0 = _mm_mul_ps(m[4][1], v[1]);
    t1 = _mm_mul_ps(m[5][1], v[1]);
    t2 = _mm_mul_ps(m[6][1], v[1]);
    t3 = _mm_mul_ps(m[7][1], v[1]);

    t0 = _mm_hadd_ps(t0, t1);
    t2 = _mm_hadd_ps(t2, t3);
    r3 = _mm_hadd_ps(t0, t2);

    r[0] = _mm_add_ps(r0, r1);
    r[1] = _mm_add_ps(r2, r3);
}

As for alignment, a variable of a type __m128 should be automatically aligned on the stack. With dynamic memory, this is not a safe assumption. Some malloc / new implementations may only return memory guaranteed to be 8-byte aligned.

The intrinsics header provides _mm_malloc and _mm_free. The align parameter should be (16) in this case.

回答2:

Intel has developed a Small Matrix Library for matrices with sizes ranging from 1×1 to 6×6. Application Note AP-930 Streaming SIMD Extensions - Matrix Multiplication describes in detail the algorithm for multiplying two 6×6 matrices. This should be adaptable to other size matrices with some effort.