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Grid/tests/lanczos/BlockProjector.h

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2017-10-26 01:59:59 +01:00
namespace Grid {
/*
BlockProjector
If _HP_BLOCK_PROJECTORS_ is defined, we assume that _evec is a basis that is not
fully orthonormalized (to the precision of the coarse field) and we allow for higher-precision
coarse field than basis field.
*/
//#define _HP_BLOCK_PROJECTORS_
template<typename Field>
class BlockProjector {
public:
BasisFieldVector<Field>& _evec;
BlockedGrid<Field>& _bgrid;
BlockProjector(BasisFieldVector<Field>& evec, BlockedGrid<Field>& bgrid) : _evec(evec), _bgrid(bgrid) {
}
void createOrthonormalBasis(RealD thres = 0.0) {
GridStopWatch sw;
sw.Start();
int cnt = 0;
#pragma omp parallel shared(cnt)
{
int lcnt = 0;
#pragma omp for
for (int b=0;b<_bgrid._o_blocks;b++) {
for (int i=0;i<_evec._Nm;i++) {
auto nrm0 = _bgrid.block_sp(b,_evec._v[i],_evec._v[i]);
// |i> -= <j|i> |j>
for (int j=0;j<i;j++) {
_bgrid.block_caxpy(b,_evec._v[i],-_bgrid.block_sp(b,_evec._v[j],_evec._v[i]),_evec._v[j],_evec._v[i]);
}
auto nrm = _bgrid.block_sp(b,_evec._v[i],_evec._v[i]);
auto eps = nrm/nrm0;
if (Reduce(eps).real() < thres) {
lcnt++;
}
// TODO: if norm is too small, remove this eigenvector/mark as not needed; in practice: set it to zero norm here and return a mask
// that is then used later to decide not to write certain eigenvectors to disk (add a norm calculation before subtraction step and look at nrm/nrm0 < eps to decide)
_bgrid.block_cscale(b,1.0 / sqrt(nrm),_evec._v[i]);
}
}
#pragma omp critical
{
cnt += lcnt;
}
}
sw.Stop();
std::cout << GridLogMessage << "Gram-Schmidt to create blocked basis took " << sw.Elapsed() << " (" << ((RealD)cnt / (RealD)_bgrid._o_blocks / (RealD)_evec._Nm)
<< " below threshold)" << std::endl;
}
template<typename CoarseField>
void coarseToFine(const CoarseField& in, Field& out) {
out = zero;
out.checkerboard = _evec._v[0].checkerboard;
int Nbasis = sizeof(in._odata[0]._internal._internal) / sizeof(in._odata[0]._internal._internal[0]);
assert(Nbasis == _evec._Nm);
#pragma omp parallel for
for (int b=0;b<_bgrid._o_blocks;b++) {
for (int j=0;j<_evec._Nm;j++) {
_bgrid.block_caxpy(b,out,in._odata[b]._internal._internal[j],_evec._v[j],out);
}
}
}
template<typename CoarseField>
void fineToCoarse(const Field& in, CoarseField& out) {
out = zero;
int Nbasis = sizeof(out._odata[0]._internal._internal) / sizeof(out._odata[0]._internal._internal[0]);
assert(Nbasis == _evec._Nm);
Field tmp(_bgrid._grid);
tmp = in;
#pragma omp parallel for
for (int b=0;b<_bgrid._o_blocks;b++) {
for (int j=0;j<_evec._Nm;j++) {
// |rhs> -= <j|rhs> |j>
auto c = _bgrid.block_sp(b,_evec._v[j],tmp);
_bgrid.block_caxpy(b,tmp,-c,_evec._v[j],tmp); // may make this more numerically stable
out._odata[b]._internal._internal[j] = c;
}
}
}
template<typename CoarseField>
void deflateFine(BasisFieldVector<CoarseField>& _coef,const std::vector<RealD>& eval,int N,const Field& src_orig,Field& result) {
result = zero;
for (int i=0;i<N;i++) {
Field tmp(result._grid);
coarseToFine(_coef._v[i],tmp);
axpy(result,TensorRemove(innerProduct(tmp,src_orig)) / eval[i],tmp,result);
}
}
template<typename CoarseField>
void deflateCoarse(BasisFieldVector<CoarseField>& _coef,const std::vector<RealD>& eval,int N,const Field& src_orig,Field& result) {
CoarseField src_coarse(_coef._v[0]._grid);
CoarseField result_coarse = src_coarse;
result_coarse = zero;
fineToCoarse(src_orig,src_coarse);
for (int i=0;i<N;i++) {
axpy(result_coarse,TensorRemove(innerProduct(_coef._v[i],src_coarse)) / eval[i],_coef._v[i],result_coarse);
}
coarseToFine(result_coarse,result);
}
template<typename CoarseField>
void deflate(BasisFieldVector<CoarseField>& _coef,const std::vector<RealD>& eval,int N,const Field& src_orig,Field& result) {
// Deflation on coarse Grid is much faster, so use it by default. Deflation on fine Grid is kept for legacy reasons for now.
deflateCoarse(_coef,eval,N,src_orig,result);
}
};
}