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Imported changes from feature/gparity_HMC branch:

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Rework of WilsonFlow class
		Fixed logic error in smear method where the step index was initialized to 1 rather than 0, resulting in the logged output value of tau being too large by epsilon
		Previously smear_adaptive would maintain the current value of tau as a class member variable whereas smear would compute it separately; now both methods maintain the current value internally and it is updated by the evolve_step routines. Both evolve methods are now const.
		smear_adaptive now also maintains the current value of epsilon internally, allowing it to be a const method and also allowing the same class instance to be reused without needing to be reset
		Replaced the fixed evaluation of the plaquette energy density and plaquette topological charge during the smearing with a highly flexible general strategy where the user can add arbitrary measurements as functional objects that are evaluated at an arbitrary frequency
	        By default the same plaquette-based measurements are performed, but additional example functions are provided where the smearing is performed with different choices of measurement that are returned as an array for further processing
		Added a method to compute the energy density using the Cloverleaf approach which has smaller discretization errors
	Added a new tensor utility operation, copyLane, which allows for the copying of a single SIMD lane between two instances of the same tensor type but potentially different precisions
	To LocalCoherenceLanczos, added the option to compute the high/low eval of the fine operator on every restart to aid in tuning the Chebyshev
	Added Test_field_array_io which demonstrates and tests a single-file write of an arbitrary array of fields
	Added Test_evec_compression which generates evecs using Lanczos and attempts to compress them using the local coherence technique
	Added Test_compressed_lanczos_gparity which demonstrates the local coherence Lanczos for G-parity BCs
	Added HMC main programs for the 40ID and 48ID G-parity lattices
This commit is contained in:
Christopher Kelly
2022-07-01 14:10:59 -04:00
parent fd933420c6
commit 33e4a0caee
9 changed files with 3247 additions and 57 deletions
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19
Grid/algorithms/iterative/LocalCoherenceLanczos.h
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@ -146,14 +146,21 @@ public:
LinearOperatorBase<FineField> &_Linop;
RealD _coarse_relax_tol;
std::vector<FineField> &_subspace;
int _largestEvalIdxForReport; //The convergence of the LCL is based on the evals of the coarse grid operator, not those of the underlying fine grid operator
//As a result we do not know what the eval range of the fine operator is until the very end, making tuning the Cheby bounds very difficult
//To work around this issue, every restart we separately reconstruct the fine operator eval for the lowest and highest evec and print these
//out alongside the evals of the coarse operator. To do so we need to know the index of the largest eval (i.e. Nstop-1)
//NOTE: If largestEvalIdxForReport=-1 (default) then this is not performed
ImplicitlyRestartedLanczosSmoothedTester(LinearFunction<CoarseField> &Poly,
OperatorFunction<FineField> &smoother,
LinearOperatorBase<FineField> &Linop,
std::vector<FineField> &subspace,
RealD coarse_relax_tol=5.0e3)
RealD coarse_relax_tol=5.0e3,
int largestEvalIdxForReport=-1)
: _smoother(smoother), _Linop(Linop), _Poly(Poly), _subspace(subspace),
_coarse_relax_tol(coarse_relax_tol)
_coarse_relax_tol(coarse_relax_tol), _largestEvalIdxForReport(largestEvalIdxForReport)
{ };
//evalMaxApprox: approximation of largest eval of the fine Chebyshev operator (suitably wrapped by block projection)
@ -179,6 +186,12 @@ public:
<<" |H B[i] - eval[i]B[i]|^2 / evalMaxApprox^2 " << std::setw(25) << vv
<<std::endl;
if(_largestEvalIdxForReport != -1 && (j==0 || j==_largestEvalIdxForReport)){
std::cout<<GridLogIRL << "Estimating true eval of fine grid operator for eval idx " << j << std::endl;
RealD tmp_eval;
ReconstructEval(j,eresid,B,tmp_eval,1.0); //don't use evalMaxApprox of coarse operator! (cf below)
}
int conv=0;
if( (vv<eresid*eresid) ) conv = 1;
return conv;
@ -409,7 +422,7 @@ public:
//////////////////////////////////////////////////////////////////////////////////////////////////
Chebyshev<FineField> ChebySmooth(cheby_smooth); //lower order Chebyshev of fine operator on fine grid used to smooth regenerated eigenvectors
ImplicitlyRestartedLanczosSmoothedTester<Fobj,CComplex,nbasis> ChebySmoothTester(ChebyOp,ChebySmooth,_FineOp,subspace,relax);
ImplicitlyRestartedLanczosSmoothedTester<Fobj,CComplex,nbasis> ChebySmoothTester(ChebyOp,ChebySmooth,_FineOp,subspace,relax,Nstop-1);
evals_coarse.resize(Nm);
evec_coarse.resize(Nm,_CoarseGrid);

2
Grid/qcd/observables/topological_charge.h
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@ -99,7 +99,7 @@ public:
// using wilson flow by default here
WilsonFlow<PeriodicGimplR> WF(Pars.Smearing.steps, Pars.Smearing.step_size, Pars.Smearing.meas_interval);
WF.smear_adaptive(Usmear, U, Pars.Smearing.maxTau);
Real T0 = WF.energyDensityPlaquette(Usmear);
Real T0 = WF.energyDensityPlaquette(Pars.Smearing.maxTau, Usmear);
std::cout << GridLogMessage << std::setprecision(std::numeric_limits<Real>::digits10 + 1)
<< "T0 : [ " << traj << " ] "<< T0 << std::endl;
}

200
Grid/qcd/smearing/WilsonFlow.h
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@ -7,6 +7,7 @@ Source file: ./lib/qcd/modules/plaquette.h
Copyright (C) 2017
Author: Guido Cossu <guido.cossu@ed.ac.uk>
Author: Christopher Kelly <ckelly@bnl.gov>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
@ -33,28 +34,44 @@ NAMESPACE_BEGIN(Grid);
template <class Gimpl>
class WilsonFlow: public Smear<Gimpl>{
public:
//Store generic measurements to take during smearing process using std::function
typedef std::function<void(int, RealD, const typename Gimpl::GaugeField &)> FunctionType; //int: step, RealD: flow time, GaugeField : the gauge field
private:
unsigned int Nstep;
unsigned int measure_interval;
mutable RealD epsilon, taus;
RealD epsilon; //for regular smearing this is the time step, for adaptive it is the initial time step
std::vector< std::pair<int, FunctionType> > functions; //The int maps to the measurement frequency
mutable WilsonGaugeAction<Gimpl> SG;
void evolve_step(typename Gimpl::GaugeField&) const;
void evolve_step_adaptive(typename Gimpl::GaugeField&, RealD);
RealD tau(unsigned int t)const {return epsilon*(t+1.0); }
//Evolve the gauge field by 1 step and update tau
void evolve_step(typename Gimpl::GaugeField &U, RealD &tau) const;
//Evolve the gauge field by 1 step and update tau and the current time step eps
void evolve_step_adaptive(typename Gimpl::GaugeField&U, RealD &tau, RealD &eps, RealD maxTau) const;
public:
INHERIT_GIMPL_TYPES(Gimpl)
void resetActions(){ functions.clear(); }
void addMeasurement(int meas_interval, FunctionType meas){ functions.push_back({meas_interval, meas}); }
//Set the class to perform the default measurements:
//the plaquette energy density every step
//the plaquette topological charge every 'topq_meas_interval' steps
//and output to stdout
void setDefaultMeasurements(int topq_meas_interval = 1);
explicit WilsonFlow(unsigned int Nstep, RealD epsilon, unsigned int interval = 1):
Nstep(Nstep),
epsilon(epsilon),
measure_interval(interval),
SG(WilsonGaugeAction<Gimpl>(3.0)) {
// WilsonGaugeAction with beta 3.0
assert(epsilon > 0.0);
LogMessage();
setDefaultMeasurements(interval);
}
void LogMessage() {
@ -73,9 +90,29 @@ public:
// undefined for WilsonFlow
}
void smear_adaptive(GaugeField&, const GaugeField&, RealD maxTau);
RealD energyDensityPlaquette(unsigned int step, const GaugeField& U) const;
RealD energyDensityPlaquette(const GaugeField& U) const;
void smear_adaptive(GaugeField&, const GaugeField&, RealD maxTau) const;
//Compute t^2 <E(t)> for time t from the plaquette
static RealD energyDensityPlaquette(const RealD t, const GaugeField& U);
//Compute t^2 <E(t)> for time t from the 1x1 cloverleaf form
//t is the Wilson flow time
static RealD energyDensityCloverleaf(const RealD t, const GaugeField& U);
//Evolve the gauge field by Nstep steps of epsilon and return the energy density computed every interval steps
//The smeared field is output as V
std::vector<RealD> flowMeasureEnergyDensityPlaquette(GaugeField &V, const GaugeField& U, int measure_interval = 1);
//Version that does not return the smeared field
std::vector<RealD> flowMeasureEnergyDensityPlaquette(const GaugeField& U, int measure_interval = 1);
//Evolve the gauge field by Nstep steps of epsilon and return the Cloverleaf energy density computed every interval steps
//The smeared field is output as V
std::vector<RealD> flowMeasureEnergyDensityCloverleaf(GaugeField &V, const GaugeField& U, int measure_interval = 1);
//Version that does not return the smeared field
std::vector<RealD> flowMeasureEnergyDensityCloverleaf(const GaugeField& U, int measure_interval = 1);
};
@ -83,7 +120,7 @@ public:
// Implementations
////////////////////////////////////////////////////////////////////////////////
template <class Gimpl>
void WilsonFlow<Gimpl>::evolve_step(typename Gimpl::GaugeField &U) const{
void WilsonFlow<Gimpl>::evolve_step(typename Gimpl::GaugeField &U, RealD &tau) const{
GaugeField Z(U.Grid());
GaugeField tmp(U.Grid());
SG.deriv(U, Z);
@ -99,12 +136,13 @@ void WilsonFlow<Gimpl>::evolve_step(typename Gimpl::GaugeField &U) const{
SG.deriv(U, tmp); Z += tmp; // 4/3*(17/36*Z0 -8/9*Z1) +Z2
Z *= 3.0/4.0; // Z = 17/36*Z0 -8/9*Z1 +3/4*Z2
Gimpl::update_field(Z, U, -2.0*epsilon); // V(t+e) = exp(ep*Z)*W2
tau += epsilon;
}
template <class Gimpl>
void WilsonFlow<Gimpl>::evolve_step_adaptive(typename Gimpl::GaugeField &U, RealD maxTau) {
if (maxTau - taus < epsilon){
epsilon = maxTau-taus;
void WilsonFlow<Gimpl>::evolve_step_adaptive(typename Gimpl::GaugeField &U, RealD &tau, RealD &eps, RealD maxTau) const{
if (maxTau - tau < eps){
eps = maxTau-tau;
}
//std::cout << GridLogMessage << "Integration epsilon : " << epsilon << std::endl;
GaugeField Z(U.Grid());
@ -114,95 +152,151 @@ void WilsonFlow<Gimpl>::evolve_step_adaptive(typename Gimpl::GaugeField &U, Real
SG.deriv(U, Z);
Zprime = -Z;
Z *= 0.25; // Z0 = 1/4 * F(U)
Gimpl::update_field(Z, U, -2.0*epsilon); // U = W1 = exp(ep*Z0)*W0
Gimpl::update_field(Z, U, -2.0*eps); // U = W1 = exp(ep*Z0)*W0
Z *= -17.0/8.0;
SG.deriv(U, tmp); Z += tmp; // -17/32*Z0 +Z1
Zprime += 2.0*tmp;
Z *= 8.0/9.0; // Z = -17/36*Z0 +8/9*Z1
Gimpl::update_field(Z, U, -2.0*epsilon); // U_= W2 = exp(ep*Z)*W1
Gimpl::update_field(Z, U, -2.0*eps); // U_= W2 = exp(ep*Z)*W1
Z *= -4.0/3.0;
SG.deriv(U, tmp); Z += tmp; // 4/3*(17/36*Z0 -8/9*Z1) +Z2
Z *= 3.0/4.0; // Z = 17/36*Z0 -8/9*Z1 +3/4*Z2
Gimpl::update_field(Z, U, -2.0*epsilon); // V(t+e) = exp(ep*Z)*W2
Gimpl::update_field(Z, U, -2.0*eps); // V(t+e) = exp(ep*Z)*W2
// Ramos
Gimpl::update_field(Zprime, Uprime, -2.0*epsilon); // V'(t+e) = exp(ep*Z')*W0
Gimpl::update_field(Zprime, Uprime, -2.0*eps); // V'(t+e) = exp(ep*Z')*W0
// Compute distance as norm^2 of the difference
GaugeField diffU = U - Uprime;
RealD diff = norm2(diffU);
// adjust integration step
taus += epsilon;
tau += eps;
//std::cout << GridLogMessage << "Adjusting integration step with distance: " << diff << std::endl;
epsilon = epsilon*0.95*std::pow(1e-4/diff,1./3.);
eps = eps*0.95*std::pow(1e-4/diff,1./3.);
//std::cout << GridLogMessage << "New epsilon : " << epsilon << std::endl;
}
template <class Gimpl>
RealD WilsonFlow<Gimpl>::energyDensityPlaquette(unsigned int step, const GaugeField& U) const {
RealD td = tau(step);
return 2.0 * td * td * SG.S(U)/U.Grid()->gSites();
RealD WilsonFlow<Gimpl>::energyDensityPlaquette(const RealD t, const GaugeField& U){
static WilsonGaugeAction<Gimpl> SG(3.0);
return 2.0 * t * t * SG.S(U)/U.Grid()->gSites();
}
//Compute t^2 <E(t)> for time from the 1x1 cloverleaf form
template <class Gimpl>
RealD WilsonFlow<Gimpl>::energyDensityCloverleaf(const RealD t, const GaugeField& U){
typedef typename Gimpl::GaugeLinkField GaugeMat;
typedef typename Gimpl::GaugeField GaugeLorentz;
assert(Nd == 4);
//E = 1/2 tr( F_munu F_munu )
//However as F_numu = -F_munu, only need to sum the trace of the squares of the following 6 field strengths:
//F_01 F_02 F_03 F_12 F_13 F_23
GaugeMat F(U.Grid());
LatticeComplexD R(U.Grid());
R = Zero();
for(int mu=0;mu<3;mu++){
for(int nu=mu+1;nu<4;nu++){
WilsonLoops<Gimpl>::FieldStrength(F, U, mu, nu);
R = R + trace(F*F);
}
}
ComplexD out = sum(R);
out = t*t*out / RealD(U.Grid()->gSites());
return -real(out); //minus sign necessary for +ve energy
}
template <class Gimpl>
std::vector<RealD> WilsonFlow<Gimpl>::flowMeasureEnergyDensityPlaquette(GaugeField &V, const GaugeField& U, int measure_interval){
std::vector<RealD> out;
resetActions();
addMeasurement(measure_interval, [&out](int step, RealD t, const typename Gimpl::GaugeField &U){
std::cout << GridLogMessage << "[WilsonFlow] Computing plaquette energy density for step " << step << std::endl;
out.push_back( energyDensityPlaquette(t,U) );
});
smear(V,U);
return out;
}
template <class Gimpl>
RealD WilsonFlow<Gimpl>::energyDensityPlaquette(const GaugeField& U) const {
return 2.0 * taus * taus * SG.S(U)/U.Grid()->gSites();
std::vector<RealD> WilsonFlow<Gimpl>::flowMeasureEnergyDensityPlaquette(const GaugeField& U, int measure_interval){
GaugeField V(U);
return flowMeasureEnergyDensityPlaquette(V,U, measure_interval);
}
template <class Gimpl>
std::vector<RealD> WilsonFlow<Gimpl>::flowMeasureEnergyDensityCloverleaf(GaugeField &V, const GaugeField& U, int measure_interval){
std::vector<RealD> out;
resetActions();
addMeasurement(measure_interval, [&out](int step, RealD t, const typename Gimpl::GaugeField &U){
std::cout << GridLogMessage << "[WilsonFlow] Computing Cloverleaf energy density for step " << step << std::endl;
out.push_back( energyDensityCloverleaf(t,U) );
});
smear(V,U);
return out;
}
template <class Gimpl>
std::vector<RealD> WilsonFlow<Gimpl>::flowMeasureEnergyDensityCloverleaf(const GaugeField& U, int measure_interval){
GaugeField V(U);
return flowMeasureEnergyDensityCloverleaf(V,U, measure_interval);
}
//#define WF_TIMING
template <class Gimpl>
void WilsonFlow<Gimpl>::smear(GaugeField& out, const GaugeField& in) const {
void WilsonFlow<Gimpl>::smear(GaugeField& out, const GaugeField& in) const{
out = in;
for (unsigned int step = 1; step <= Nstep; step++) {
RealD taus = 0.;
for (unsigned int step = 1; step <= Nstep; step++) { //step indicates the number of smearing steps applied at the time of measurement
auto start = std::chrono::high_resolution_clock::now();
evolve_step(out);
evolve_step(out, taus);
auto end = std::chrono::high_resolution_clock::now();
std::chrono::duration<double> diff = end - start;
#ifdef WF_TIMING
std::cout << "Time to evolve " << diff.count() << " s\n";
#endif
std::cout << GridLogMessage << "[WilsonFlow] Energy density (plaq) : "
<< step << " " << tau(step) << " "
<< energyDensityPlaquette(step,out) << std::endl;
if( step % measure_interval == 0){
std::cout << GridLogMessage << "[WilsonFlow] Top. charge : "
<< step << " "
<< WilsonLoops<PeriodicGimplR>::TopologicalCharge(out) << std::endl;
}
//Perform measurements
for(auto const &meas : functions)
if( step % meas.first == 0 ) meas.second(step,taus,out);
}
}
template <class Gimpl>
void WilsonFlow<Gimpl>::smear_adaptive(GaugeField& out, const GaugeField& in, RealD maxTau){
void WilsonFlow<Gimpl>::smear_adaptive(GaugeField& out, const GaugeField& in, RealD maxTau) const{
out = in;
taus = epsilon;
RealD taus = 0.;
RealD eps = epsilon;
unsigned int step = 0;
do{
step++;
//std::cout << GridLogMessage << "Evolution time :"<< taus << std::endl;
evolve_step_adaptive(out, maxTau);
std::cout << GridLogMessage << "[WilsonFlow] Energy density (plaq) : "
<< step << " " << taus << " "
<< energyDensityPlaquette(out) << std::endl;
if( step % measure_interval == 0){
std::cout << GridLogMessage << "[WilsonFlow] Top. charge : "
<< step << " "
<< WilsonLoops<PeriodicGimplR>::TopologicalCharge(out) << std::endl;
}
evolve_step_adaptive(out, taus, eps, maxTau);
//Perform measurements
for(auto const &meas : functions)
if( step % meas.first == 0 ) meas.second(step,taus,out);
} while (taus < maxTau);
}
template <class Gimpl>
void WilsonFlow<Gimpl>::setDefaultMeasurements(int topq_meas_interval){
addMeasurement(1, [](int step, RealD t, const typename Gimpl::GaugeField &U){
std::cout << GridLogMessage << "[WilsonFlow] Energy density (plaq) : " << step << " " << t << " " << energyDensityPlaquette(t,U) << std::endl;
});
addMeasurement(topq_meas_interval, [](int step, RealD t, const typename Gimpl::GaugeField &U){
std::cout << GridLogMessage << "[WilsonFlow] Top. charge : " << step << " " << WilsonLoops<Gimpl>::TopologicalCharge(U) << std::endl;
});
}
NAMESPACE_END(Grid);

41
Grid/tensors/Tensor_extract_merge.h
View File

@ -208,5 +208,46 @@ void merge(vobj &vec,const ExtractPointerArray<sobj> &extracted, int offset)
}
//////////////////////////////////////////////////////////////////////////////////
//Copy a single lane of a SIMD tensor type from one object to another
//Output object must be of the same tensor type but may be of a different precision (i.e. it can have a different root data type)
///////////////////////////////////////////////////////////////////////////////////
template<class vobjOut, class vobjIn>
accelerator_inline
void copyLane(vobjOut & __restrict__ vecOut, int lane_out, const vobjIn & __restrict__ vecIn, int lane_in)
{
static_assert( std::is_same<typename vobjOut::DoublePrecision, typename vobjIn::DoublePrecision>::value == 1, "copyLane: tensor types must be the same" ); //if tensor types are same the DoublePrecision type must be the same
typedef typename vobjOut::vector_type ovector_type;
typedef typename vobjIn::vector_type ivector_type;
constexpr int owords=sizeof(vobjOut)/sizeof(ovector_type);
constexpr int iwords=sizeof(vobjIn)/sizeof(ivector_type);
static_assert( owords == iwords, "copyLane: Expected number of vector words in input and output objects to be equal" );
typedef typename vobjOut::scalar_type oscalar_type;
typedef typename vobjIn::scalar_type iscalar_type;
typedef typename ExtractTypeMap<oscalar_type>::extract_type oextract_type;
typedef typename ExtractTypeMap<iscalar_type>::extract_type iextract_type;
typedef oextract_type * opointer;
typedef iextract_type * ipointer;
constexpr int oNsimd=ovector_type::Nsimd();
constexpr int iNsimd=ivector_type::Nsimd();
iscalar_type itmp;
oscalar_type otmp;
opointer __restrict__ op = (opointer)&vecOut;
ipointer __restrict__ ip = (ipointer)&vecIn;
for(int w=0;w<owords;w++){
memcpy( (char*)&itmp, (char*)(ip + lane_in + iNsimd*w), sizeof(iscalar_type) );
otmp = itmp; //potential precision change
memcpy( (char*)(op + lane_out + oNsimd*w), (char*)&otmp, sizeof(oscalar_type) );
}
}
NAMESPACE_END(Grid);