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Annoying, cannot rely on equivalence of Grid ComplexD adn Eigen Complex type on GPU.

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Solve with ComplexD typecasts but must be a better way
This commit is contained in:
Peter Boyle
2019-06-04 20:47:49 +01:00
parent 6e2e904a0e
commit 7a1569bd46
9 changed files with 76 additions and 66 deletions
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28
Grid/algorithms/iterative/CommunicationAvoidingGeneralisedMinimalResidual.h
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@ -54,10 +54,10 @@ class CommunicationAvoidingGeneralisedMinimalResidual : public OperatorFunction<
Eigen::MatrixXcd H;
std::vector<std::complex<double>> y;
std::vector<std::complex<double>> gamma;
std::vector<std::complex<double>> c;
std::vector<std::complex<double>> s;
std::vector<ComplexD> y;
std::vector<ComplexD> gamma;
std::vector<ComplexD> c;
std::vector<ComplexD> s;
CommunicationAvoidingGeneralisedMinimalResidual(RealD tol,
Integer maxit,
@ -159,7 +159,9 @@ class CommunicationAvoidingGeneralisedMinimalResidual : public OperatorFunction<
gamma[0] = sqrt(norm2(r));
v[0] = (1. / gamma[0]) * r;
ComplexD scale = 1.0/gamma[0];
v[0] = scale * r;
LinalgTimer.Stop();
for (int i=0; i<RestartLength; i++) {
@ -170,7 +172,7 @@ class CommunicationAvoidingGeneralisedMinimalResidual : public OperatorFunction<
qrUpdate(i);
cp = std::norm(gamma[i+1]);
cp = norm(gamma[i+1]);
std::cout << GridLogIterative << "CommunicationAvoidingGeneralisedMinimalResidual: Iteration " << IterationCount
<< " residual " << cp << " target " << rsq << std::endl;
@ -196,11 +198,11 @@ class CommunicationAvoidingGeneralisedMinimalResidual : public OperatorFunction<
LinalgTimer.Start();
for (int i = 0; i <= iter; ++i) {
H(iter, i) = innerProduct(v[i], w);
w = w - H(iter, i) * v[i];
w = w - ComplexD(H(iter, i)) * v[i];
}
H(iter, iter + 1) = sqrt(norm2(w));
v[iter + 1] = (1. / H(iter, iter + 1)) * w;
v[iter + 1] = ComplexD(1. / H(iter, iter + 1)) * w;
LinalgTimer.Stop();
}
@ -208,8 +210,8 @@ class CommunicationAvoidingGeneralisedMinimalResidual : public OperatorFunction<
QrTimer.Start();
for (int i = 0; i < iter ; ++i) {
auto tmp = -s[i] * H(iter, i) + c[i] * H(iter, i + 1);
H(iter, i) = std::conj(c[i]) * H(iter, i) + std::conj(s[i]) * H(iter, i + 1);
auto tmp = -s[i] * ComplexD(H(iter, i)) + c[i] * ComplexD(H(iter, i + 1));
H(iter, i) = conjugate(c[i]) * ComplexD(H(iter, i)) + conjugate(s[i]) * ComplexD(H(iter, i + 1));
H(iter, i + 1) = tmp;
}
@ -223,7 +225,7 @@ class CommunicationAvoidingGeneralisedMinimalResidual : public OperatorFunction<
H(iter, iter + 1) = 0.;
gamma[iter + 1] = -s[iter] * gamma[iter];
gamma[iter] = std::conj(c[iter]) * gamma[iter];
gamma[iter] = conjugate(c[iter]) * gamma[iter];
QrTimer.Stop();
}
@ -233,8 +235,8 @@ class CommunicationAvoidingGeneralisedMinimalResidual : public OperatorFunction<
for (int i = iter; i >= 0; i--) {
y[i] = gamma[i];
for (int k = i + 1; k <= iter; k++)
y[i] = y[i] - H(k, i) * y[k];
y[i] = y[i] / H(i, i);
y[i] = y[i] - ComplexD(H(k, i)) * y[k];
y[i] = y[i] / ComplexD(H(i, i));
}
for (int i = 0; i <= iter; i++)