myGEMM1 kernel doesn't seem to work properly

[MattiaCacciatore]

https:/CNugteren/myGEMM/blame/e2a364537f2b8725b3f5ba5f81008d04558a2327/extra/minimal.cpp#L39

The function seems to compute the multiplication in the wrong order, i just assume that from my tests. The fix should be:

"__kernel void gpu_matrix_mult(const int M, const int N, const int K, const __global float* A, const __global float* B, __global float* C){"
    "    const int globalRow = get_global_id(0);"
    "    const int globalCol = get_global_id(1);"
    "    float acc = 0;"
    "    for (int i=0; i<N; ++i){"
    "        acc += A[globalRow*N + i] * B[i*K + globalCol];"
    "    }"
    "    C[globalRow*K + globalCol] = acc;"
    "}";

Computing the multiplication with CPU and/or just testing it with SIZE 4/8 printing A B and C matrices and do some hand calculating, it should show a different result. The function i've used:

void cpu_matrix_mult(const float* const c_a, const float* const c_b, float* c_c, const int m, const int n, const int k){
    float sum = 0;
    for (int i = 0; i < m; ++i){
        for (int j = 0; j < k; ++j){
            sum = 0;
            for (int h = 0; h < n; ++h){
                sum += c_a[i * n + h] * c_b[h * k + j];
            }
            c_c[i * k + j] = sum;
        }
    }
}

[CNugteren]

I guess you mean column-major versus row-major? That should be explained in the tutorial on page 2:

We assume data to be stored in column-major format (Fortran-style), following cuBLAS's default. If we wanted, we could easily change this to row-major by swapping the A and B matrices and the N and M constants, so this is not a real limitation of our code.