public static void ConjugateGradient(FloatResidentArray X, SparseMatrix A, FloatResidentArray B, int maxiter, float eps)
{
int N = (int)B.Count;
FloatResidentArray R = new FloatResidentArray(N);
FloatResidentArray P = new FloatResidentArray(N);
FloatResidentArray AP = new FloatResidentArray(N);
A.RefreshDevice();
X.RefreshDevice();
B.RefreshDevice();
wrapper.Fmsub(R, B, A, X, N); // R = B - A*X
wrapper.Copy(P, R, N);
int k = 0;
while (k < maxiter)
{
wrapper.Multiply(AP, A, P, N); // AP = A*P
float r = ScalarProd(R, R, N); // save <R|R>
float alpha = r / ScalarProd(P, AP, N); // alpha = <R|R> / <P|AP>
wrapper.Saxpy(X, X, alpha, P, N); // X = X - alpha*P
wrapper.Saxpy(R, R, -alpha, AP, N); // RR = R-alpha*AP
float rr = ScalarProd(R, R, N);
if (rr < eps * eps)
{
break;
}
float beta = rr / r;
wrapper.Saxpy(P, R, beta, P, N); // P = R + beta*P
++k;
}
X.RefreshHost();
}
public void RefreshHost()
{
indices.RefreshHost();
data.RefreshHost();
rows.RefreshHost();
}
public void RefreshHost()
{
_inner.RefreshHost();
}