/*
* Solves lapl(u) x = b, for x, given b, using Conjugate Gradient
*/
void
cg(latparams lp, field **x, field **b, link **g)
{
size_t L = lp.L;
int max_iter = 100;
float tol = 1e-9;
/* Temporary fields needed for CG */
field **r = new_field(lp);
field **p = new_field(lp);
field **Ap = new_field(lp);
/* Initial residual and p-vector */
lapl(lp, r, x, g);
xmy(lp, b, r);
xeqy(lp, p, r);
/* Initial r-norm and b-norm */
float rr = xdotx(lp, r);
float bb = xdotx(lp, b);
double t_lapl = 0;
int iter = 0;
for(iter=0; iter<max_iter; iter++) {
printf(" %6d, res = %+e\n", iter, rr/bb);
if(sqrt(rr/bb) < tol)
break;
double t = stop_watch(0);
lapl(lp, Ap, p, g);
t_lapl += stop_watch(t);
float pAp = xdoty(lp, p, Ap);
float alpha = rr/pAp;
axpy(lp, alpha, p, x);
axpy(lp, -alpha, Ap, r);
float r1r1 = xdotx(lp, r);
float beta = r1r1/rr;
xpay(lp, r, beta, p);
rr = r1r1;
}
/* Recompute residual after convergence */
lapl(lp, r, x, g);
xmy(lp, b, r);
rr = xdotx(lp, r);
double beta_fp = 50*((double)L*L*L)/(t_lapl/(double)iter)*1e-9;
double beta_io = 40*((double)L*L*L)/(t_lapl/(double)iter)*1e-9;
printf(" Converged after %6d iterations, res = %+e\n", iter, rr/bb);
printf(" Time in lapl(): %+6.3e sec/call, %4.2e Gflop/s, %4.2e GB/s\n",
t_lapl/(double)iter, beta_fp, beta_io);
del_field(r);
del_field(p);
del_field(Ap);
return;
}
/*
* Solves lapl(u) x = b, for x, given b, using Conjugate Gradient
*/
void
cg(size_t L, _Complex float *x, _Complex float *b, _Complex float *u)
{
int max_iter = 100;
float tol = 1e-6;
/* Temporary fields needed for CG */
_Complex float *r = new_field(L);
_Complex float *p = new_field(L);
_Complex float *Ap = new_field(L);
/* Initial residual and p-vector */
lapl(L, r, x, u);
xmy(L, b, r);
xeqy(L, p, r);
/* Initial r-norm and b-norm */
float rr = xdotx(L, r);
float bb = xdotx(L, b);
double t_lapl = 0;
int iter = 0;
for(iter=0; iter<max_iter; iter++) {
printf(" %6d, res = %+e\n", iter, rr/bb);
if(sqrt(rr/bb) < tol)
break;
double t = stop_watch(0);
lapl(L, Ap, p, u);
t_lapl += stop_watch(t);
float pAp = xdoty(L, p, Ap);
float alpha = rr/pAp;
axpy(L, alpha, p, x);
axpy(L, -alpha, Ap, r);
float r1r1 = xdotx(L, r);
float beta = r1r1/rr;
xpay(L, r, beta, p);
rr = r1r1;
}
/* Recompute residual after convergence */
lapl(L, r, x, u);
xmy(L, b, r);
rr = xdotx(L, r);
double beta_fp = 34*L*L/(t_lapl/(double)iter)*1e-9;
double beta_io = 32*L*L/(t_lapl/(double)iter)*1e-9;
printf(" Converged after %6d iterations, res = %+e\n", iter, rr/bb);
printf(" Time in lapl(): %+6.3e sec/call, %4.2e Gflop/s, %4.2e GB/s\n",
t_lapl/(double)iter, beta_fp, beta_io);
free(r);
free(p);
free(Ap);
return;
}
int
main()
{
DenseVector sings;
GeMat deltas(3,2);
std::vector<GeMat> _deltas;
Function x2f(x2, sings);
Function onef(one, sings);
Function x3f(x3, sings);
Function cosf(mycos, sings);
Function sinf(mysin, sings);
Function expf(myexp, sings);
Basis basis(4);
basis.template enforceBoundaryCondition<lawa::DirichletBC>();
IndexSet indexset;
Coeff1D coeff;
std::vector<Function> fvec;
int rank = 2;
int dim = 64;
for (int i=1; i<=32; ++i) {
fvec.push_back(cosf);
fvec.push_back(onef);
fvec.push_back(x2f);
fvec.push_back(onef);
}
SepCoeff coeffs(rank, dim);
IndexSetVec indexsetvec(dim);
lawa::SeparableFunctionD<T> F(fvec, rank, dim);
MatInt derivs(rank, dim);
for (int i=1; i<=rank; ++i) {
for (int j=1; j<=dim; ++j) {
derivs(i,j) = 0;
_deltas.push_back(deltas);
}
}
lawa::SeparableRHSD<T, Basis> Fint(basis, F, _deltas, derivs);
getFullIndexSet(basis, indexset, 2);
std::cout << "The index set size is\n" << indexset.size()
<< std::endl;
for (int l=0; (unsigned)l<indexsetvec.size(); ++l) {
indexsetvec[l] = indexset;
}
/* Map */
lawa::Mapwavind<Index1D> map(dim);
map.rehash(50);
genCoefficients(coeffs, Fint, indexsetvec);
lawa::HTCoefficients<T, Basis> f(dim, basis, map);
lawa::HTCoefficients<T, Basis> u(dim, basis, map);
lawa::HTCoefficients<T, Basis> r(dim, basis, map);
Laplace1D LaplaceBil(basis);
RefLaplace1D RefLaplaceBil(basis.refinementbasis);
Identity1D IdentityBil(basis);
RefIdentity1D RefIdentityBil(basis.refinementbasis);
LOp_Lapl1D lapl(basis, basis, RefLaplaceBil, LaplaceBil);
Sepop A(lapl, dim, dim);
lawa::Sepdiagscal<Basis> S(dim, basis);
setScaling(S, 0.5);
lawa::HTAWGM_Params params;
params.maxit_pcg = 100;
params.maxit_awgm = 100;
params.tol_awgm = 1e-08;
params.delta1_pcg = 1e-01;
params.delta2_pcg = 1e-01;
params.delta3_pcg = 1e-01;
params.alpha = 0.95;
params.recompr = 1e-02;
params.gamma = 0.1;
params.theta = 1e-08;
std::cout << "HTAWGM params =\n";
std::cout << params << std::endl;
unsigned its;
double res;
its = htawgm(A, S, u, Fint, indexsetvec, res, params);
std::cout << "htawgm took " << its << " iterations to reach "
<< res << " accuracy" << std::endl;
std::cout << "Final scaling set to\n" << S << std::endl;
return 0;
}
bool VMCcuda::run() {
if (UseDrift == "yes")
return runWithDrift();
resetRun();
IndexType block = 0;
IndexType nAcceptTot = 0;
IndexType nRejectTot = 0;
IndexType updatePeriod= (QMCDriverMode[QMC_UPDATE_MODE])
? Period4CheckProperties
: (nBlocks+1)*nSteps;
int nat = W.getTotalNum();
int nw = W.getActiveWalkers();
vector<RealType> LocalEnergy(nw);
vector<PosType> delpos(nw);
vector<PosType> newpos(nw);
vector<ValueType> ratios(nw);
vector<GradType> oldG(nw), newG(nw);
vector<ValueType> oldL(nw), newL(nw);
vector<Walker_t*> accepted(nw);
Matrix<ValueType> lapl(nw, nat);
Matrix<GradType> grad(nw, nat);
double Esum;
// First do warmup steps
for (int step=0; step<myWarmupSteps; step++) {
for(int iat=0; iat<nat; ++iat) {
//create a 3N-Dimensional Gaussian with variance=1
makeGaussRandomWithEngine(delpos,Random);
for(int iw=0; iw<nw; ++iw) {
PosType G = W[iw]->Grad[iat];
newpos[iw]=W[iw]->R[iat] + m_sqrttau*delpos[iw];
ratios[iw] = 1.0;
}
W.proposeMove_GPU(newpos, iat);
Psi.ratio(W,iat,ratios,newG, newL);
accepted.clear();
vector<bool> acc(nw, false);
for(int iw=0; iw<nw; ++iw) {
if(ratios[iw]*ratios[iw] > Random()) {
accepted.push_back(W[iw]);
nAccept++;
W[iw]->R[iat] = newpos[iw];
acc[iw] = true;
}
else
nReject++;
}
W.acceptMove_GPU(acc);
if (accepted.size())
Psi.update(accepted,iat);
}
}
do {
IndexType step = 0;
nAccept = nReject = 0;
Esum = 0.0;
Estimators->startBlock(nSteps);
do
{
++step;
++CurrentStep;
for (int isub=0; isub<nSubSteps; isub++) {
for(int iat=0; iat<nat; ++iat) {
//create a 3N-Dimensional Gaussian with variance=1
makeGaussRandomWithEngine(delpos,Random);
for(int iw=0; iw<nw; ++iw) {
PosType G = W[iw]->Grad[iat];
newpos[iw]=W[iw]->R[iat] + m_sqrttau*delpos[iw];
ratios[iw] = 1.0;
}
W.proposeMove_GPU(newpos, iat);
Psi.ratio(W,iat,ratios,newG, newL);
accepted.clear();
vector<bool> acc(nw, false);
for(int iw=0; iw<nw; ++iw) {
if(ratios[iw]*ratios[iw] > Random()) {
accepted.push_back(W[iw]);
nAccept++;
W[iw]->R[iat] = newpos[iw];
acc[iw] = true;
}
else
nReject++;
}
W.acceptMove_GPU(acc);
if (accepted.size())
Psi.update(accepted,iat);
}
}
Psi.gradLapl(W, grad, lapl);
H.evaluate (W, LocalEnergy);
if (myPeriod4WalkerDump && (CurrentStep % myPeriod4WalkerDump)==0)
W.saveEnsemble();
Estimators->accumulate(W);
} while(step<nSteps);
Psi.recompute(W);
// vector<RealType> logPsi(W.WalkerList.size(), 0.0);
// Psi.evaluateLog(W, logPsi);
double accept_ratio = (double)nAccept/(double)(nAccept+nReject);
Estimators->stopBlock(accept_ratio);
nAcceptTot += nAccept;
nRejectTot += nReject;
++block;
recordBlock(block);
} while(block<nBlocks);
//Mover->stopRun();
//finalize a qmc section
return finalize(block);
}
bool VMCcuda::runWithDrift()
{
resetRun();
IndexType block = 0;
IndexType nAcceptTot = 0;
IndexType nRejectTot = 0;
int nat = W.getTotalNum();
int nw = W.getActiveWalkers();
vector<RealType> LocalEnergy(nw), oldScale(nw), newScale(nw);
vector<PosType> delpos(nw);
vector<PosType> dr(nw);
vector<PosType> newpos(nw);
vector<ValueType> ratios(nw), rplus(nw), rminus(nw);
vector<PosType> oldG(nw), newG(nw);
vector<ValueType> oldL(nw), newL(nw);
vector<Walker_t*> accepted(nw);
Matrix<ValueType> lapl(nw, nat);
Matrix<GradType> grad(nw, nat);
// First, do warmup steps
for (int step=0; step<myWarmupSteps; step++) {
for(int iat=0; iat<nat; iat++) {
Psi.getGradient (W, iat, oldG);
//create a 3N-Dimensional Gaussian with variance=1
makeGaussRandomWithEngine(delpos,Random);
for(int iw=0; iw<nw; iw++) {
oldScale[iw] = getDriftScale(m_tauovermass,oldG[iw]);
dr[iw] = (m_sqrttau*delpos[iw]) + (oldScale[iw]*oldG[iw]);
newpos[iw]=W[iw]->R[iat] + dr[iw];
ratios[iw] = 1.0;
}
W.proposeMove_GPU(newpos, iat);
Psi.ratio(W,iat,ratios,newG, newL);
accepted.clear();
vector<bool> acc(nw, false);
for(int iw=0; iw<nw; ++iw) {
PosType drOld =
newpos[iw] - (W[iw]->R[iat] + oldScale[iw]*oldG[iw]);
RealType logGf = -m_oneover2tau * dot(drOld, drOld);
newScale[iw] = getDriftScale(m_tauovermass,newG[iw]);
PosType drNew =
(newpos[iw] + newScale[iw]*newG[iw]) - W[iw]->R[iat];
RealType logGb = -m_oneover2tau * dot(drNew, drNew);
RealType x = logGb - logGf;
RealType prob = ratios[iw]*ratios[iw]*std::exp(x);
if(Random() < prob) {
accepted.push_back(W[iw]);
nAccept++;
W[iw]->R[iat] = newpos[iw];
acc[iw] = true;
}
else
nReject++;
}
W.acceptMove_GPU(acc);
if (accepted.size())
Psi.update(accepted,iat);
}
}
// Now do data collection steps
do {
IndexType step = 0;
nAccept = nReject = 0;
Estimators->startBlock(nSteps);
do {
step++;
CurrentStep++;
for (int isub=0; isub<nSubSteps; isub++) {
for(int iat=0; iat<nat; iat++) {
Psi.getGradient (W, iat, oldG);
//create a 3N-Dimensional Gaussian with variance=1
makeGaussRandomWithEngine(delpos,Random);
for(int iw=0; iw<nw; iw++) {
oldScale[iw] = getDriftScale(m_tauovermass,oldG[iw]);
dr[iw] = (m_sqrttau*delpos[iw]) + (oldScale[iw]*oldG[iw]);
newpos[iw]=W[iw]->R[iat] + dr[iw];
ratios[iw] = 1.0;
}
W.proposeMove_GPU(newpos, iat);
Psi.ratio(W,iat,ratios,newG, newL);
accepted.clear();
vector<bool> acc(nw, false);
for(int iw=0; iw<nw; ++iw) {
PosType drOld =
newpos[iw] - (W[iw]->R[iat] + oldScale[iw]*oldG[iw]);
// if (dot(drOld, drOld) > 25.0)
// cerr << "Large drift encountered! Old drift = " << drOld << endl;
RealType logGf = -m_oneover2tau * dot(drOld, drOld);
newScale[iw] = getDriftScale(m_tauovermass,newG[iw]);
PosType drNew =
(newpos[iw] + newScale[iw]*newG[iw]) - W[iw]->R[iat];
// if (dot(drNew, drNew) > 25.0)
// cerr << "Large drift encountered! Drift = " << drNew << endl;
RealType logGb = -m_oneover2tau * dot(drNew, drNew);
RealType x = logGb - logGf;
RealType prob = ratios[iw]*ratios[iw]*std::exp(x);
if(Random() < prob) {
accepted.push_back(W[iw]);
nAccept++;
W[iw]->R[iat] = newpos[iw];
acc[iw] = true;
}
else
nReject++;
}
W.acceptMove_GPU(acc);
if (accepted.size())
Psi.update(accepted,iat);
}
// cerr << "Rank = " << myComm->rank() <<
// " CurrentStep = " << CurrentStep << " isub = " << isub << endl;
}
Psi.gradLapl(W, grad, lapl);
H.evaluate (W, LocalEnergy);
if (myPeriod4WalkerDump && (CurrentStep % myPeriod4WalkerDump)==0)
W.saveEnsemble();
Estimators->accumulate(W);
} while(step<nSteps);
Psi.recompute(W);
double accept_ratio = (double)nAccept/(double)(nAccept+nReject);
Estimators->stopBlock(accept_ratio);
nAcceptTot += nAccept;
nRejectTot += nReject;
++block;
recordBlock(block);
} while(block<nBlocks);
//finalize a qmc section
if (!myComm->rank())
gpu::cuda_memory_manager.report();
return finalize(block);
}
bool DMCcuda::run()
{
bool NLmove = NonLocalMove == "yes";
bool scaleweight = ScaleWeight == "yes";
if (NLmove)
app_log() << " Using Casula nonlocal moves in DMCcuda.\n";
if (scaleweight)
app_log() << " Scaling weight per Umrigar/Nightengale.\n";
resetRun();
Mover->MaxAge = 1;
IndexType block = 0;
IndexType nAcceptTot = 0;
IndexType nRejectTot = 0;
int nat = W.getTotalNum();
int nw = W.getActiveWalkers();
vector<RealType> LocalEnergy(nw), LocalEnergyOld(nw),
oldScale(nw), newScale(nw);
vector<PosType> delpos(nw);
vector<PosType> dr(nw);
vector<PosType> newpos(nw);
vector<ValueType> ratios(nw), rplus(nw), rminus(nw), R2prop(nw), R2acc(nw);
vector<PosType> oldG(nw), newG(nw);
vector<ValueType> oldL(nw), newL(nw);
vector<Walker_t*> accepted(nw);
Matrix<ValueType> lapl(nw, nat);
Matrix<GradType> grad(nw, nat);
vector<ValueType> V2(nw), V2bar(nw);
vector<vector<NonLocalData> > Txy(nw);
for (int iw=0; iw<nw; iw++)
W[iw]->Weight = 1.0;
do {
IndexType step = 0;
nAccept = nReject = 0;
Estimators->startBlock(nSteps);
do {
step++;
CurrentStep++;
nw = W.getActiveWalkers();
ResizeTimer.start();
LocalEnergy.resize(nw); oldScale.resize(nw);
newScale.resize(nw); delpos.resize(nw);
dr.resize(nw); newpos.resize(nw);
ratios.resize(nw); rplus.resize(nw);
rminus.resize(nw); oldG.resize(nw);
newG.resize(nw); oldL.resize(nw);
newL.resize(nw); accepted.resize(nw);
lapl.resize(nw, nat); grad.resize(nw, nat);
R2prop.resize(nw,0.0); R2acc.resize(nw,0.0);
V2.resize(nw,0.0); V2bar.resize(nw,0.0);
W.updateLists_GPU();
ResizeTimer.stop();
if (NLmove) {
Txy.resize(nw);
for (int iw=0; iw<nw; iw++) {
Txy[iw].clear();
Txy[iw].push_back(NonLocalData(-1, 1.0, PosType()));
}
}
for (int iw=0; iw<nw; iw++)
W[iw]->Age++;
DriftDiffuseTimer.start();
for(int iat=0; iat<nat; iat++) {
Psi.getGradient (W, iat, oldG);
//create a 3N-Dimensional Gaussian with variance=1
makeGaussRandomWithEngine(delpos,Random);
for(int iw=0; iw<nw; iw++) {
delpos[iw] *= m_sqrttau;
oldScale[iw] = getDriftScale(m_tauovermass,oldG[iw]);
dr[iw] = delpos[iw] + (oldScale[iw]*oldG[iw]);
newpos[iw]=W[iw]->R[iat] + dr[iw];
ratios[iw] = 1.0;
R2prop[iw] += dot(delpos[iw], delpos[iw]);
}
W.proposeMove_GPU(newpos, iat);
Psi.ratio(W,iat,ratios,newG, newL);
accepted.clear();
vector<bool> acc(nw, false);
for(int iw=0; iw<nw; ++iw) {
PosType drOld =
newpos[iw] - (W[iw]->R[iat] + oldScale[iw]*oldG[iw]);
RealType logGf = -m_oneover2tau * dot(drOld, drOld);
newScale[iw] = getDriftScale(m_tauovermass,newG[iw]);
PosType drNew =
(newpos[iw] + newScale[iw]*newG[iw]) - W[iw]->R[iat];
RealType logGb = -m_oneover2tau * dot(drNew, drNew);
RealType x = logGb - logGf;
RealType prob = ratios[iw]*ratios[iw]*std::exp(x);
if(Random() < prob && ratios[iw] > 0.0) {
accepted.push_back(W[iw]);
nAccept++;
W[iw]->R[iat] = newpos[iw];
W[iw]->Age = 0;
acc[iw] = true;
R2acc[iw] += dot(delpos[iw], delpos[iw]);
V2[iw] += m_tauovermass * m_tauovermass * dot(newG[iw],newG[iw]);
V2bar[iw] += newScale[iw] * newScale[iw] * dot(newG[iw],newG[iw]);
}
else {
nReject++;
V2[iw] += m_tauovermass * m_tauovermass * dot(oldG[iw],oldG[iw]);
V2bar[iw] += oldScale[iw] * oldScale[iw] * dot(oldG[iw],oldG[iw]);
}
}
W.acceptMove_GPU(acc);
if (accepted.size())
Psi.update(accepted,iat);
}
DriftDiffuseTimer.stop();
// Psi.recompute(W, false);
Psi.gradLapl(W, grad, lapl);
HTimer.start();
if (NLmove) H.evaluate (W, LocalEnergy, Txy);
else H.evaluate (W, LocalEnergy);
HTimer.stop();
// for (int iw=0; iw<nw; iw++) {
// branchEngine->clampEnergy(LocalEnergy[iw]);
// W[iw]->getPropertyBase()[LOCALENERGY] = LocalEnergy[iw];
// }
if (CurrentStep == 1)
LocalEnergyOld = LocalEnergy;
if (NLmove) {
// Now, attempt nonlocal move
accepted.clear();
vector<int> iatList;
vector<PosType> accPos;
for (int iw=0; iw<nw; iw++) {
/// HACK HACK HACK
// if (LocalEnergy[iw] < -2300.0) {
// cerr << "Walker " << iw << " has energy "
// << LocalEnergy[iw] << endl;;
// double maxWeight = 0.0;
// int elMax = -1;
// PosType posMax;
// for (int j=1; j<Txy[iw].size(); j++)
// if (std::fabs(Txy[iw][j].Weight) > std::fabs(maxWeight)) {
// maxWeight = Txy[iw][j].Weight;
// elMax = Txy[iw][j].PID;
// posMax = W[iw]->R[elMax] + Txy[iw][j].Delta;
// }
// cerr << "Maximum weight is " << maxWeight << " for electron "
// << elMax << " at position " << posMax << endl;
// PosType unit = W.Lattice.toUnit(posMax);
// unit[0] -= round(unit[0]);
// unit[1] -= round(unit[1]);
// unit[2] -= round(unit[2]);
// cerr << "Reduced position = " << unit << endl;
// }
int ibar = NLop.selectMove(Random(), Txy[iw]);
if (ibar) {
accepted.push_back(W[iw]);
int iat = Txy[iw][ibar].PID;
iatList.push_back(iat);
accPos.push_back(W[iw]->R[iat] + Txy[iw][ibar].Delta);
}
}
if (accepted.size()) {
Psi.ratio(accepted,iatList, accPos, ratios, newG, newL);
Psi.update(accepted,iatList);
for (int i=0; i<accepted.size(); i++)
accepted[i]->R[iatList[i]] = accPos[i];
W.NLMove_GPU (accepted, accPos, iatList);
// HACK HACK HACK
// Recompute the kinetic energy
// Psi.gradLapl(W, grad, lapl);
// H.evaluate (W, LocalEnergy);
//W.copyWalkersToGPU();
}
}
// Now branch
BranchTimer.start();
for (int iw=0; iw<nw; iw++) {
RealType v2=0.0, v2bar=0.0;
for(int iat=0; iat<nat; iat++) {
v2 += dot(W.G[iat],W.G[iat]);
RealType newscale = getDriftScale(m_tauovermass,newG[iw]);
v2 += m_tauovermass * m_tauovermass * dot(newG[iw],newG[iw]);
v2bar += newscale * newscale * dot(newG[iw],newG[iw]);
}
//RealType scNew = std::sqrt(V2bar[iw] / V2[iw]);
RealType scNew = std::sqrt(v2bar/v2);
RealType scOld = (CurrentStep == 1) ? scNew : W[iw]->getPropertyBase()[DRIFTSCALE];
W[iw]->getPropertyBase()[DRIFTSCALE] = scNew;
// fprintf (stderr, "iw = %d scNew = %1.8f scOld = %1.8f\n", iw, scNew, scOld);
RealType tauRatio = R2acc[iw] / R2prop[iw];
if (tauRatio < 0.5)
cerr << " tauRatio = " << tauRatio << endl;
RealType taueff = m_tauovermass * tauRatio;
if (scaleweight)
W[iw]->Weight *= branchEngine->branchWeightTau
(LocalEnergy[iw], LocalEnergyOld[iw], scNew, scOld, taueff);
else
W[iw]->Weight *= branchEngine->branchWeight
(LocalEnergy[iw], LocalEnergyOld[iw]);
W[iw]->getPropertyBase()[R2ACCEPTED] = R2acc[iw];
W[iw]->getPropertyBase()[R2PROPOSED] = R2prop[iw];
}
Mover->setMultiplicity(W.begin(), W.end());
branchEngine->branch(CurrentStep,W);
nw = W.getActiveWalkers();
LocalEnergyOld.resize(nw);
for (int iw=0; iw<nw; iw++)
LocalEnergyOld[iw] = W[iw]->getPropertyBase()[LOCALENERGY];
BranchTimer.stop();
} while(step<nSteps);
Psi.recompute(W, true);
double accept_ratio = (double)nAccept/(double)(nAccept+nReject);
Estimators->stopBlock(accept_ratio);
nAcceptTot += nAccept;
nRejectTot += nReject;
++block;
recordBlock(block);
} while(block<nBlocks);
//finalize a qmc section
return finalize(block);
}
bool DMCcuda::runWithNonlocal()
{
resetRun();
Mover->MaxAge = 1;
IndexType block = 0;
IndexType nAcceptTot = 0;
IndexType nRejectTot = 0;
int nat = W.getTotalNum();
int nw = W.getActiveWalkers();
vector<RealType> LocalEnergy(nw), LocalEnergyOld(nw),
oldScale(nw), newScale(nw);
vector<PosType> delpos(nw);
vector<PosType> dr(nw);
vector<PosType> newpos(nw);
vector<ValueType> ratios(nw), rplus(nw), rminus(nw), R2prop(nw), R2acc(nw);
vector<PosType> oldG(nw), newG(nw);
vector<ValueType> oldL(nw), newL(nw);
vector<Walker_t*> accepted(nw);
Matrix<ValueType> lapl(nw, nat);
Matrix<GradType> grad(nw, nat);
vector<vector<NonLocalData> > Txy(nw);
for (int iw=0; iw<nw; iw++)
W[iw]->Weight = 1.0;
do {
IndexType step = 0;
nAccept = nReject = 0;
Estimators->startBlock(nSteps);
do {
step++;
CurrentStep++;
nw = W.getActiveWalkers();
LocalEnergy.resize(nw); oldScale.resize(nw);
newScale.resize(nw); delpos.resize(nw);
dr.resize(nw); newpos.resize(nw);
ratios.resize(nw); rplus.resize(nw);
rminus.resize(nw); oldG.resize(nw);
newG.resize(nw); oldL.resize(nw);
newL.resize(nw); accepted.resize(nw);
lapl.resize(nw, nat); grad.resize(nw, nat);
R2prop.resize(nw,0.0); R2acc.resize(nw,0.0);
W.updateLists_GPU();
Txy.resize(nw);
for (int iw=0; iw<nw; iw++) {
Txy[iw].clear();
Txy[iw].push_back(NonLocalData(-1, 1.0, PosType()));
W[iw]->Age++;
}
for(int iat=0; iat<nat; iat++) {
Psi.getGradient (W, iat, oldG);
//create a 3N-Dimensional Gaussian with variance=1
makeGaussRandomWithEngine(delpos,Random);
for(int iw=0; iw<nw; iw++) {
delpos[iw] *= m_sqrttau;
oldScale[iw] = getDriftScale(m_tauovermass,oldG[iw]);
dr[iw] = delpos[iw] + (oldScale[iw]*oldG[iw]);
newpos[iw]=W[iw]->R[iat] + dr[iw];
ratios[iw] = 1.0;
R2prop[iw] += dot(delpos[iw], delpos[iw]);
}
W.proposeMove_GPU(newpos, iat);
Psi.ratio(W,iat,ratios,newG, newL);
accepted.clear();
vector<bool> acc(nw, false);
for(int iw=0; iw<nw; ++iw) {
PosType drOld =
newpos[iw] - (W[iw]->R[iat] + oldScale[iw]*oldG[iw]);
RealType logGf = -m_oneover2tau * dot(drOld, drOld);
newScale[iw] = getDriftScale(m_tauovermass,newG[iw]);
PosType drNew =
(newpos[iw] + newScale[iw]*newG[iw]) - W[iw]->R[iat];
RealType logGb = -m_oneover2tau * dot(drNew, drNew);
RealType x = logGb - logGf;
RealType prob = ratios[iw]*ratios[iw]*std::exp(x);
if(Random() < prob && ratios[iw] > 0.0) {
accepted.push_back(W[iw]);
nAccept++;
W[iw]->R[iat] = newpos[iw];
W[iw]->Age = 0;
acc[iw] = true;
R2acc[iw] += dot(delpos[iw], delpos[iw]);
}
else
nReject++;
}
W.acceptMove_GPU(acc);
if (accepted.size())
Psi.update(accepted,iat);
}
for (int iw=0; iw < nw; iw++)
if (W[iw]->Age)
cerr << "Encountered stuck walker with iw=" << iw << endl;
// Psi.recompute(W, false);
Psi.gradLapl(W, grad, lapl);
H.evaluate (W, LocalEnergy, Txy);
if (CurrentStep == 1)
LocalEnergyOld = LocalEnergy;
// Now, attempt nonlocal move
accepted.clear();
vector<int> iatList;
vector<PosType> accPos;
for (int iw=0; iw<nw; iw++) {
int ibar = NLop.selectMove(Random(), Txy[iw]);
// cerr << "Txy[iw].size() = " << Txy[iw].size() << endl;
if (ibar) {
accepted.push_back(W[iw]);
int iat = Txy[iw][ibar].PID;
iatList.push_back(iat);
accPos.push_back(W[iw]->R[iat] + Txy[iw][ibar].Delta);
}
}
if (accepted.size()) {
// W.proposeMove_GPU(newpos, iatList);
Psi.ratio(accepted,iatList, accPos, ratios, newG, newL);
Psi.update(accepted,iatList);
for (int i=0; i<accepted.size(); i++)
accepted[i]->R[iatList[i]] = accPos[i];
W.copyWalkersToGPU();
}
// Now branch
for (int iw=0; iw<nw; iw++) {
W[iw]->Weight *= branchEngine->branchWeight(LocalEnergy[iw], LocalEnergyOld[iw]);
W[iw]->getPropertyBase()[R2ACCEPTED] = R2acc[iw];
W[iw]->getPropertyBase()[R2PROPOSED] = R2prop[iw];
}
Mover->setMultiplicity(W.begin(), W.end());
branchEngine->branch(CurrentStep,W);
nw = W.getActiveWalkers();
LocalEnergyOld.resize(nw);
for (int iw=0; iw<nw; iw++)
LocalEnergyOld[iw] = W[iw]->getPropertyBase()[LOCALENERGY];
} while(step<nSteps);
Psi.recompute(W, true);
double accept_ratio = (double)nAccept/(double)(nAccept+nReject);
Estimators->stopBlock(accept_ratio);
nAcceptTot += nAccept;
nRejectTot += nReject;
++block;
recordBlock(block);
} while(block<nBlocks);
//finalize a qmc section
return finalize(block);
}
SPOSetBase*
EinsplineSetBuilder::createSPOSet(xmlNodePtr cur)
{
//use 2 bohr as the default when truncated orbitals are used based on the extend of the ions
BufferLayer=2.0;
OhmmsAttributeSet attribs;
int numOrbs = 0;
qafm=0;
int sortBands(1);
string sourceName;
string spo_prec("double");
string truncate("no");
#if defined(QMC_CUDA)
string useGPU="yes";
#else
string useGPU="no";
#endif
attribs.add (H5FileName, "href");
attribs.add (TileFactor, "tile");
attribs.add (sortBands, "sort");
attribs.add (qafm, "afmshift");
attribs.add (TileMatrix, "tilematrix");
attribs.add (TwistNum, "twistnum");
attribs.add (givenTwist, "twist");
attribs.add (sourceName, "source");
attribs.add (MeshFactor, "meshfactor");
attribs.add (useGPU, "gpu");
attribs.add (spo_prec, "precision");
attribs.add (truncate, "truncate");
attribs.add (BufferLayer, "buffer");
attribs.put (XMLRoot);
attribs.add (numOrbs, "size");
attribs.add (numOrbs, "norbs");
attribs.put (cur);
///////////////////////////////////////////////
// Read occupation information from XML file //
///////////////////////////////////////////////
cur = cur->children;
int spinSet = -1;
vector<int> Occ_Old(0,0);
Occ.resize(0,0);
bool NewOcc(false);
while (cur != NULL)
{
string cname((const char*)(cur->name));
if(cname == "occupation")
{
string occ_mode("ground");
occ_format="energy";
particle_hole_pairs=0;
OhmmsAttributeSet oAttrib;
oAttrib.add(occ_mode,"mode");
oAttrib.add(spinSet,"spindataset");
oAttrib.add(occ_format,"format");
oAttrib.add(particle_hole_pairs,"pairs");
oAttrib.put(cur);
if(occ_mode == "excited")
{
putContent(Occ,cur);
}
else
if(occ_mode != "ground")
{
app_error() << "Only ground state occupation currently supported "
<< "in EinsplineSetBuilder.\n";
APP_ABORT("EinsplineSetBuilder::createSPOSet");
}
}
cur = cur->next;
}
if (Occ != Occ_Old)
{
NewOcc=true;
Occ_Old = Occ;
}
else
NewOcc=false;
#if defined(QMC_CUDA)
app_log() << "\t QMC_CUDA=1 Overwriting the precision of the einspline storage on the host.\n";
spo_prec="double"; //overwrite
#endif
H5OrbSet aset(H5FileName, spinSet, numOrbs);
std::map<H5OrbSet,SPOSetBase*,H5OrbSet>::iterator iter;
iter = SPOSetMap.find (aset);
if ((iter != SPOSetMap.end() ) && (!NewOcc) && (qafm==0))
{
qafm=0;
app_log() << "SPOSet parameters match in EinsplineSetBuilder: "
<< "cloning EinsplineSet object.\n";
return iter->second->makeClone();
}
// The tiling can be set by a simple vector, (e.g. 2x2x2), or by a
// full 3x3 matrix of integers. If the tilematrix was not set in
// the input file...
bool matrixNotSet = true;
for (int i=0; i<3; i++)
for (int j=0; j<3; j++)
matrixNotSet = matrixNotSet && (TileMatrix(i,j) == 0);
// then set the matrix to what may have been specified in the
// tiling vector
if (matrixNotSet)
for (int i=0; i<3; i++)
for (int j=0; j<3; j++)
TileMatrix(i,j) = (i==j) ? TileFactor(i) : 0;
if (myComm->rank() == 0)
fprintf (stderr, " [ %2d %2d %2d\n %2d %2d %2d\n %2d %2d %2d ]\n",
TileMatrix(0,0), TileMatrix(0,1), TileMatrix(0,2),
TileMatrix(1,0), TileMatrix(1,1), TileMatrix(1,2),
TileMatrix(2,0), TileMatrix(2,1), TileMatrix(2,2));
if (numOrbs == 0)
{
app_error() << "You must specify the number of orbitals in the input file.\n";
APP_ABORT("EinsplineSetBuilder::createSPOSet");
}
else
app_log() << " Reading " << numOrbs << " orbitals from HDF5 file.\n";
Timer mytimer;
mytimer.restart();
/////////////////////////////////////////////////////////////////
// Read the basic orbital information, without reading all the //
// orbitals themselves. //
/////////////////////////////////////////////////////////////////
if (myComm->rank() == 0)
if (!ReadOrbitalInfo())
{
app_error() << "Error reading orbital info from HDF5 file. Aborting.\n";
APP_ABORT("EinsplineSetBuilder::createSPOSet");
}
app_log() << "TIMER EinsplineSetBuilder::ReadOrbitalInfo " << mytimer.elapsed() << endl;
myComm->barrier();
mytimer.restart();
BroadcastOrbitalInfo();
app_log() << "TIMER EinsplineSetBuilder::BroadcastOrbitalInfo " << mytimer.elapsed() << endl;
app_log().flush();
///////////////////////////////////////////////////////////////////
// Now, analyze the k-point mesh to figure out the what k-points //
// are needed //
///////////////////////////////////////////////////////////////////
PrimCell.set(Lattice);
SuperCell.set(SuperLattice);
for (int iat=0; iat<AtomicOrbitals.size(); iat++)
AtomicOrbitals[iat].Lattice = Lattice;
// Copy supercell into the ParticleSets
// app_log() << "Overwriting XML lattice with that from the ESHDF file.\n";
// PtclPoolType::iterator piter;
// for(piter = ParticleSets.begin(); piter != ParticleSets.end(); piter++)
// piter->second->Lattice.copy(SuperCell);
AnalyzeTwists2();
//////////////////////////////////
// Create the OrbitalSet object
//////////////////////////////////
if (HaveLocalizedOrbs)
OrbitalSet = new EinsplineSetLocal;
#ifdef QMC_CUDA
else
if (AtomicOrbitals.size() > 0)
{
if (UseRealOrbitals)
OrbitalSet = new EinsplineSetHybrid<double>;
else
OrbitalSet = new EinsplineSetHybrid<complex<double> >;
}
#endif
else
{
if (UseRealOrbitals)
OrbitalSet = new EinsplineSetExtended<double>;
else
OrbitalSet = new EinsplineSetExtended<complex<double> >;
}
//set the internal parameters
setTiling(OrbitalSet,numOrbs);
if (HaveLocalizedOrbs)
{
EinsplineSetLocal *restrict orbitalSet =
dynamic_cast<EinsplineSetLocal*>(OrbitalSet);
#pragma omp critical(read_einspline_orbs)
{
if ((spinSet == LastSpinSet) && (numOrbs <= NumOrbitalsRead) && (!NewOcc) )
CopyBands(numOrbs);
else
{
// Now, figure out occupation for the bands and read them
OccupyBands(spinSet, sortBands);
ReadBands (spinSet, orbitalSet);
}
}
// Now, store what we have read
LastOrbitalSet = OrbitalSet;
LastSpinSet = spinSet;
NumOrbitalsRead = numOrbs;
}
else // Otherwise, use EinsplineSetExtended
{
mytimer.restart();
bool use_single= (spo_prec == "single" || spo_prec == "float");
if (UseRealOrbitals)
{
OccupyBands(spinSet, sortBands);
//check if a matching BsplineReaderBase exists
BsplineReaderBase* spline_reader=0;
//if(TargetPtcl.Lattice.SuperCellEnum != SUPERCELL_BULK && truncate=="yes")
if(truncate=="yes")
{
if(use_single)
{
if(TargetPtcl.Lattice.SuperCellEnum == SUPERCELL_OPEN)
spline_reader= new SplineMixedAdoptorReader<SplineOpenAdoptor<float,double,3> >(this);
else
if(TargetPtcl.Lattice.SuperCellEnum == SUPERCELL_SLAB)
spline_reader= new SplineMixedAdoptorReader<SplineMixedAdoptor<float,double,3> >(this);
else
spline_reader= new SplineAdoptorReader<SplineR2RAdoptor<float,double,3> >(this);
}
else
{
if(TargetPtcl.Lattice.SuperCellEnum == SUPERCELL_OPEN)
spline_reader= new SplineMixedAdoptorReader<SplineOpenAdoptor<double,double,3> >(this);
else
if(TargetPtcl.Lattice.SuperCellEnum == SUPERCELL_SLAB)
spline_reader= new SplineMixedAdoptorReader<SplineMixedAdoptor<double,double,3> >(this);
else
spline_reader= new SplineAdoptorReader<SplineR2RAdoptor<double,double,3> >(this);
}
}
else
{
if(use_single)
spline_reader= new SplineAdoptorReader<SplineR2RAdoptor<float,double,3> >(this);
}
if(spline_reader)
{
HasCoreOrbs=bcastSortBands(NumDistinctOrbitals,myComm->rank()==0);
SPOSetBase* bspline_zd=spline_reader->create_spline_set(spinSet,OrbitalSet);
delete spline_reader;
if(bspline_zd)
SPOSetMap[aset] = bspline_zd;
return bspline_zd;
}
else
{
app_log() << ">>>> Creating EinsplineSetExtended<double> <<<< " << endl;
EinsplineSetExtended<double> *restrict orbitalSet =
dynamic_cast<EinsplineSetExtended<double>* > (OrbitalSet);
if (Format == ESHDF)
ReadBands_ESHDF(spinSet,orbitalSet);
else
ReadBands(spinSet, orbitalSet);
}
}
else
{
OccupyBands(spinSet, sortBands);
BsplineReaderBase* spline_reader=0;
if(truncate == "yes")
{
app_log() << " Truncated orbitals with multiple kpoints are not supported yet!" << endl;
}
if(use_single)
{
#if defined(QMC_COMPLEX)
spline_reader= new SplineAdoptorReader<SplineC2CPackedAdoptor<float,double,3> >(this);
#else
spline_reader= new SplineAdoptorReader<SplineC2RPackedAdoptor<float,double,3> >(this);
#endif
}
if(spline_reader)
{
RotateBands_ESHDF(spinSet, dynamic_cast<EinsplineSetExtended<complex<double> >*>(OrbitalSet));
HasCoreOrbs=bcastSortBands(NumDistinctOrbitals,myComm->rank()==0);
SPOSetBase* bspline_zd=spline_reader->create_spline_set(spinSet,OrbitalSet);
delete spline_reader;
if(bspline_zd)
SPOSetMap[aset] = bspline_zd;
return bspline_zd;
}
else
{
EinsplineSetExtended<complex<double> > *restrict orbitalSet =
dynamic_cast<EinsplineSetExtended<complex<double> >*>(OrbitalSet);
if (Format == ESHDF)
ReadBands_ESHDF(spinSet,orbitalSet);
else
ReadBands(spinSet, orbitalSet);
}
}
app_log() << "TIMER EinsplineSetBuilder::ReadBands " << mytimer.elapsed() << endl;
}
#ifndef QMC_COMPLEX
if (myComm->rank()==0 && OrbitalSet->MuffinTins.size() > 0)
{
FILE *fout = fopen ("TestMuffins.dat", "w");
Vector<double> phi(numOrbs), lapl(numOrbs);
Vector<PosType> grad(numOrbs);
ParticleSet P;
P.R.resize(6);
for (int i=0; i<P.R.size(); i++)
P.R[i] = PosType (0.0, 0.0, 0.0);
PosType N = 0.25*PrimCell.a(0) + 0.25*PrimCell.a(1) + 0.25*PrimCell.a(2);
for (double x=-1.0; x<=1.0; x+=0.0000500113412)
{
// for (double x=-0.003; x<=0.003; x+=0.0000011329343481381) {
P.R[0] = x * (PrimCell.a(0) + 0.914*PrimCell.a(1) +
0.781413*PrimCell.a(2));
double r = std::sqrt(dot(P.R[0], P.R[0]));
double rN = std::sqrt(dot(P.R[0]-N, P.R[0]-N));
OrbitalSet->evaluate(P, 0, phi, grad, lapl);
// OrbitalSet->evaluate(P, 0, phi);
fprintf (fout, "%1.12e ", r*x/std::fabs(x));
for (int j=0; j<numOrbs; j++)
{
double gmag = std::sqrt(dot(grad[j],grad[j]));
fprintf (fout, "%16.12e ",
/*phi[j]*phi[j]**/(-5.0/r -0.5*lapl[j]/phi[j]));
// double E = -5.0/r -0.5*lapl[j]/phi[j];
fprintf (fout, "%16.12e ", phi[j]);
fprintf (fout, "%16.12e ", gmag);
}
fprintf (fout, "\n");
}
fclose(fout);
}
#endif
SPOSetMap[aset] = OrbitalSet;
if (sourceName.size() && (ParticleSets.find(sourceName) == ParticleSets.end()))
{
app_log() << " EinsplineSetBuilder creates a ParticleSet " << sourceName << endl;
ParticleSet* ions=new ParticleSet;
ions->Lattice=TargetPtcl.Lattice;
ESHDFIonsParser ap(*ions,H5FileID,myComm);
ap.put(XMLRoot);
ap.expand(TileMatrix);
ions->setName(sourceName);
ParticleSets[sourceName]=ions;
//overwrite the lattice and assign random
if(TargetPtcl.Lattice.SuperCellEnum)
{
TargetPtcl.Lattice=ions->Lattice;
makeUniformRandom(TargetPtcl.R);
TargetPtcl.R.setUnit(PosUnit::LatticeUnit);
TargetPtcl.convert2Cart(TargetPtcl.R);
TargetPtcl.createSK();
}
}
#ifdef QMC_CUDA
if (useGPU == "yes" || useGPU == "1")
{
app_log() << "Initializing GPU data structures.\n";
OrbitalSet->initGPU();
}
#endif
return OrbitalSet;
}
void STWarp<T>::warpingIteration( const WarpingField<T> &warpField,
const Video<T> &Bx,
const Video<T> &By,
const Video<T> &Bt,
const Video<T> &C,
WarpingField<T> &dWarpField) {
int height = dimensions[0];
int width = dimensions[1];
int nFrames = dimensions[2];
// int nChannels = dimensions[3];
if(params.verbosity > 1) {
fprintf(stderr, " - preparing linear system...");
}
// Differentiate (u,v,w)+d(u,v,w) in x,y,t
WarpingField<T> warpDX(warpField.size());
WarpingField<T> warpDY(warpField.size());
WarpingField<T> warpDT(warpField.size());
WarpingField<T> warpTotal(warpField);
warpTotal.add(dWarpField);
VideoProcessing::dx(warpTotal,warpDX);
VideoProcessing::dy(warpTotal,warpDY);
VideoProcessing::dt(warpTotal,warpDT);
// Compute smoothness cost
Video<T> smoothCost(height, width, nFrames, 9);
Video<T> lapl(warpField.size());
computeSmoothCost(warpDX, warpDY, warpDT, warpField, smoothCost, lapl);
computeOcclusion(warpTotal, C, occlusion);
// Compute data cost
Video<T> dataCost;
if(params.useFeatures){
dataCost = Video<T>(height,width,nFrames,2);
}else{
dataCost = Video<T>(height,width,nFrames,1);
}
computeDataCost(Bx, By, Bt, C, dWarpField, occlusion, dataCost);
// Prepare system
Video<T> CBx(height,width,nFrames,1);
Video<T> CBy(height,width,nFrames,1);
Video<T> CBt(height,width,nFrames,1);
Video<T> Bx2(height,width,nFrames,1);
Video<T> By2(height,width,nFrames,1);
Video<T> Bt2(height,width,nFrames,1);
Video<T> Bxy(height,width,nFrames,1);
Video<T> Bxt(height,width,nFrames,1);
Video<T> Byt(height,width,nFrames,1);
prepareLinearSystem(Bx, By, Bt, C, lapl, dataCost,
CBx, CBy, CBt, Bx2, By2, Bt2,
Bxy, Bxt, Byt);
if(params.verbosity > 1) {
fprintf(stderr, "done.\n");
}
if(params.verbosity > 1) {
fprintf(stderr, " - SOR...");
}
sor( dataCost, smoothCost, lapl,
CBx, CBy, CBt, Bx2,
By2, Bt2, Bxy, Bxt, Byt, dWarpField);
if(params.verbosity > 1) {
fprintf(stderr, "done.\n");
}
}
