C++ for Scientists - Technische Universität Dresden

5.4. META-TUNING: WRITE YOUR OWN COMPILER OPTIMIZATION 163
w[1]+= A[1][1] ∗ v[1];
w[2]+= A[2][1] ∗ v[1];
w[3]+= A[3][1] ∗ v[1];
w[0]+= A[0][2] ∗ v[2];
w[1]+= A[1][2] ∗ v[2];
w[2]+= A[2][2] ∗ v[2];
w[3]+= A[3][2] ∗ v[2];
w[0]+= A[0][3] ∗ v[3];
w[1]+= A[1][3] ∗ v[3];
w[2]+= A[2][3] ∗ v[3];
w[3]+= A[3][3] ∗ v[3];
We only need to reorganize our functor. The general template reads now:
template
struct fsize mat vec mult cm
{
template
void operator()(const Matrix& A, const VecIn& v in, VecOut& v out)
{
fsize mat vec mult cm()(A, v in, v out);
v out[Rows]+= A[Rows][Cols] ∗ v in[Cols];
}
};
Now, we need a partial specialization for row 0 to go the next column:
template
struct fsize mat vec mult cm
{
template
void operator()(const Matrix& A, const VecIn& v in, VecOut& v out)
{
fsize mat vec mult cm()(A, v in, v out);
v out[0]+= A[0][Cols] ∗ v in[Cols];
}
};
The partial specialization for column 0 is also needed to initialize the entry of the output vector:
template
struct fsize mat vec mult cm
{
template
void operator()(const Matrix& A, const VecIn& v in, VecOut& v out)
{
fsize mat vec mult cm()(A, v in, v out);
v out[Rows]= A[Rows][0] ∗ v in[0];
}
};
Finally, we still need a specialization for row and column 0 to terminate the recursion. This
can be reused from the previous functor:
template
struct fsize mat vec mult cm
: fsize mat vec mult {};