C++ for Scientists - Technische Universität Dresden

5.4. META-TUNING: WRITE YOUR OWN COMPILER OPTIMIZATION 181
}
mult block block;
for (unsigned i= 0; i < s; i+= Size0)
for (unsigned k= 0; k < s; k+= Size1) {
multi tmp tmp(value type(0));
for (unsigned j= 0; j < s; j++)
block(tmp, A, B, i, j, k);
block.update(tmp, C, i, k);
}
We still owe the reader the implementation of the functor mult block. The techniques are the
same as in vector operations but we have to deal with more indices and their respective limits:
template
struct mult block
{
typedef mult block next;
template
void operator()(Tmp& tmp, const Matrix& A, const Matrix& B, unsigned i, unsigned j, unsigned k)
{
std::cout ≪ ”tmp.” ≪ tmp.bs ≪ ”+= A[” ≪ i + Index0 ≪ ”][” ≪ j ≪ ”] ∗ B[” ≪ j ≪ ”][” ≪
k + Index1 ≪ ”]\n”;
tmp.value+= A(i + Index0, j) ∗ B(j, k + Index1);
next()(tmp.sub, A, B, i, j, k);
}
};
template
void update(const Tmp& tmp, Matrix& C, unsigned i, unsigned k)
{
std::cout ≪ ”C[” ≪ i + Index0 ≪ ”][” ≪ k + Index1 ≪ ”]= tmp.” ≪ tmp.bs ≪ ”\n”;
C(i + Index0, k + Index1)= tmp.value;
next().update(tmp.sub, C, i, k);
}
template
struct mult block
{
typedef mult block next;
template
void operator()(Tmp& tmp, const Matrix& A, const Matrix& B, unsigned i, unsigned j, unsigned k)
{
std::cout ≪ ”tmp.” ≪ tmp.bs ≪ ”+= A[” ≪ i + Index0 ≪ ”][” ≪ j ≪ ”] ∗ B[” ≪ j ≪ ”][” ≪
k + Max1 ≪ ”]\n”;
tmp.value+= A(i + Index0, j) ∗ B(j, k + Max1);
next()(tmp.sub, A, B, i, j, k);
}
template
void update(const Tmp& tmp, Matrix& C, unsigned i, unsigned k)
{
std::cout ≪ ”C[” ≪ i + Index0 ≪ ”][” ≪ k + Max1 ≪ ”]= tmp.” ≪ tmp.bs ≪ ”\n”;