SSE Matrix Multiplication NxN. Why is this error - c

Question

I am beginner using SSE instructions, and I try to implement MMM. So, I implemented MMM using matriz 2by2, now I want to implement MMM using matrix NXN
#include <emmintrin.h>
#include <stdio.h>
#include <stdlib.h>
void simd_2x2(int lda, double *A, double *B, double *C)
{
__m128d a, b1, c1;
for (int k = 0; k < lda; k++) {
//printf("%f\n",C[k * lda]);
c1 = _mm_loadu_pd(C + k * lda); //load unaligned block in C
//c2 = _mm_loadu_pd(C + 1 * lda);
for (int i = 0; i < lda; ++i) {
a = _mm_load_pd(A + i * lda);//load aligned i-th column of A
b1 = _mm_load1_pd(B + i + k * lda); //load i-th row of B
//b2 = _mm_load1_pd(B + i + 1 * lda);
c1 = _mm_add_pd(c1, _mm_mul_pd(a, b1)); //rank-1 update
//c2 = _mm_add_pd(c2, _mm_mul_pd(a, b2));
}
_mm_storeu_pd(C + k * lda, c1); //store unaligned block in C
//_mm_storeu_pd(C + 1 * lda, c2);
}
}
int main() {
int n = 2;
double *buf = NULL;
buf = (double *)malloc(3 * n * n * sizeof(double));
double *A = buf + 0;
double *B = A + n * n;
double *C = B + n * n;
simd_2x2(n, A, B, C);
return 0;
}
When n=2 everything work fine:
A = 4.000000 3.000000
2.000000 4.000000
B = 1.000000 3.000000
2.000000 4.000000
C = 0.000000 0.000000
0.000000 0.000000
C = C + A * B = 10.000000 24.000000
10.000000 22.000000
but if n=4 I get the next:
A = 4.000000 0.000000 1.000000 4.000000
2.000000 1.000000 4.000000 0.000000
3.000000 1.000000 2.000000 1.000000
4.000000 1.000000 3.000000 1.000000
B = 1.000000 5.000000 9.000000 13.000000
2.000000 6.000000 10.000000 14.000000
3.000000 7.000000 11.000000 15.000000
4.000000 8.000000 12.000000 16.000000
C = 0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000
C = C + A * B = 23.000000 59.000000 95.000000 131.000000
16.000000 44.000000 72.000000 100.000000
0.000000 0.000000 0.000000 0.000000
0.000000 0.000000 0.000000 0.000000
The last two rows are not calculated, why is this? Can someone help me?
I have almost 5 days reading about SSE but I can not fully understand and neither solve this problem.