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Faster linalg on CG optimised against staggered

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Sum overhead is bigger for staggered
This commit is contained in:
Azusa Yamaguchi 2018-04-26 10:07:19 +01:00
parent eac6ec4b5e
commit 3e125c5b61
1 changed files with 19 additions and 12 deletions
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31
lib/algorithms/iterative/ConjugateGradient.h
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@ -70,7 +70,6 @@ class ConjugateGradient : public OperatorFunction<Field> {
Linop.HermOpAndNorm(psi, mmp, d, b); Linop.HermOpAndNorm(psi, mmp, d, b);
r = src - mmp; r = src - mmp;
p = r; p = r;
@ -97,6 +96,9 @@ class ConjugateGradient : public OperatorFunction<Field> {
<< "ConjugateGradient: k=0 residual " << cp << " target " << rsq << std::endl; << "ConjugateGradient: k=0 residual " << cp << " target " << rsq << std::endl;
GridStopWatch LinalgTimer; GridStopWatch LinalgTimer;
GridStopWatch InnerTimer;
GridStopWatch AxpyNormTimer;
GridStopWatch LinearCombTimer;
GridStopWatch MatrixTimer; GridStopWatch MatrixTimer;
GridStopWatch SolverTimer; GridStopWatch SolverTimer;
@ -106,30 +108,32 @@ class ConjugateGradient : public OperatorFunction<Field> {
c = cp; c = cp;
MatrixTimer.Start(); MatrixTimer.Start();
Linop.HermOpAndNorm(p, mmp, d, qq); Linop.HermOp(p, mmp);
MatrixTimer.Stop(); MatrixTimer.Stop();
LinalgTimer.Start(); LinalgTimer.Start();
// AA
// RealD qqck = norm2(mmp);
// ComplexD dck = innerProduct(p,mmp);
InnerTimer.Start();
ComplexD dc = innerProduct(p,mmp);
InnerTimer.Stop();
d = dc.real();
a = c / d; a = c / d;
b_pred = a * (a * qq - d) / c;
AxpyNormTimer.Start();
cp = axpy_norm(r, -a, mmp, r); cp = axpy_norm(r, -a, mmp, r);
AxpyNormTimer.Stop();
b = cp / c; b = cp / c;
// Fuse these loops ; should be really easy LinearCombTimer.Start();
psi = a * p + psi; parallel_for(int ss=0;ss<src._grid->oSites();ss++){
p = p * b + r; vstream(psi[ss], a * p[ss] + psi[ss]);
vstream(p [ss], b * p[ss] + r[ss]);
}
LinearCombTimer.Stop();
LinalgTimer.Stop(); LinalgTimer.Stop();
std::cout << GridLogIterative << "ConjugateGradient: Iteration " << k std::cout << GridLogIterative << "ConjugateGradient: Iteration " << k
<< " residual " << cp << " target " << rsq << std::endl; << " residual " << cp << " target " << rsq << std::endl;
std::cout << GridLogDebug << "a = "<< a << " b_pred = "<< b_pred << " b = "<< b << std::endl;
std::cout << GridLogDebug << "qq = "<< qq << " d = "<< d << " c = "<< c << std::endl;
// Stopping condition // Stopping condition
if (cp <= rsq) { if (cp <= rsq) {
@ -150,6 +154,9 @@ class ConjugateGradient : public OperatorFunction<Field> {
std::cout << GridLogMessage << "\tElapsed " << SolverTimer.Elapsed() <<std::endl; std::cout << GridLogMessage << "\tElapsed " << SolverTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\tMatrix " << MatrixTimer.Elapsed() <<std::endl; std::cout << GridLogMessage << "\tMatrix " << MatrixTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\tLinalg " << LinalgTimer.Elapsed() <<std::endl; std::cout << GridLogMessage << "\tLinalg " << LinalgTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\tInner " << InnerTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\tAxpyNorm " << AxpyNormTimer.Elapsed() <<std::endl;
std::cout << GridLogMessage << "\tLinearComb " << LinearCombTimer.Elapsed() <<std::endl;
if (ErrorOnNoConverge) assert(true_residual / Tolerance < 10000.0); if (ErrorOnNoConverge) assert(true_residual / Tolerance < 10000.0);