mirror of
https://github.com/paboyle/Grid.git
synced 2024-11-16 02:35:36 +00:00
144 lines
4.1 KiB
C++
144 lines
4.1 KiB
C++
namespace Grid {
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/*
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BlockProjector
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If _HP_BLOCK_PROJECTORS_ is defined, we assume that _evec is a basis that is not
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fully orthonormalized (to the precision of the coarse field) and we allow for higher-precision
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coarse field than basis field.
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*/
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//#define _HP_BLOCK_PROJECTORS_
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template<typename Field>
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class BlockProjector {
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public:
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BasisFieldVector<Field>& _evec;
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BlockedGrid<Field>& _bgrid;
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BlockProjector(BasisFieldVector<Field>& evec, BlockedGrid<Field>& bgrid) : _evec(evec), _bgrid(bgrid) {
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}
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void createOrthonormalBasis(RealD thres = 0.0) {
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GridStopWatch sw;
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sw.Start();
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int cnt = 0;
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#pragma omp parallel shared(cnt)
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{
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int lcnt = 0;
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#pragma omp for
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for (int b=0;b<_bgrid._o_blocks;b++) {
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for (int i=0;i<_evec._Nm;i++) {
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auto nrm0 = _bgrid.block_sp(b,_evec._v[i],_evec._v[i]);
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// |i> -= <j|i> |j>
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for (int j=0;j<i;j++) {
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_bgrid.block_caxpy(b,_evec._v[i],-_bgrid.block_sp(b,_evec._v[j],_evec._v[i]),_evec._v[j],_evec._v[i]);
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}
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auto nrm = _bgrid.block_sp(b,_evec._v[i],_evec._v[i]);
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auto eps = nrm/nrm0;
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if (Reduce(eps).real() < thres) {
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lcnt++;
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}
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// 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
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// 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)
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_bgrid.block_cscale(b,1.0 / sqrt(nrm),_evec._v[i]);
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}
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}
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#pragma omp critical
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{
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cnt += lcnt;
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}
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}
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sw.Stop();
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std::cout << GridLogMessage << "Gram-Schmidt to create blocked basis took " << sw.Elapsed() << " (" << ((RealD)cnt / (RealD)_bgrid._o_blocks / (RealD)_evec._Nm)
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<< " below threshold)" << std::endl;
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}
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template<typename CoarseField>
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void coarseToFine(const CoarseField& in, Field& out) {
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out = zero;
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out.checkerboard = _evec._v[0].checkerboard;
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int Nbasis = sizeof(in._odata[0]._internal._internal) / sizeof(in._odata[0]._internal._internal[0]);
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assert(Nbasis == _evec._Nm);
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#pragma omp parallel for
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for (int b=0;b<_bgrid._o_blocks;b++) {
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for (int j=0;j<_evec._Nm;j++) {
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_bgrid.block_caxpy(b,out,in._odata[b]._internal._internal[j],_evec._v[j],out);
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}
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}
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}
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template<typename CoarseField>
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void fineToCoarse(const Field& in, CoarseField& out) {
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out = zero;
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int Nbasis = sizeof(out._odata[0]._internal._internal) / sizeof(out._odata[0]._internal._internal[0]);
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assert(Nbasis == _evec._Nm);
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Field tmp(_bgrid._grid);
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tmp = in;
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#pragma omp parallel for
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for (int b=0;b<_bgrid._o_blocks;b++) {
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for (int j=0;j<_evec._Nm;j++) {
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// |rhs> -= <j|rhs> |j>
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auto c = _bgrid.block_sp(b,_evec._v[j],tmp);
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_bgrid.block_caxpy(b,tmp,-c,_evec._v[j],tmp); // may make this more numerically stable
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out._odata[b]._internal._internal[j] = c;
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}
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}
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}
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template<typename CoarseField>
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void deflateFine(BasisFieldVector<CoarseField>& _coef,const std::vector<RealD>& eval,int N,const Field& src_orig,Field& result) {
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result = zero;
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for (int i=0;i<N;i++) {
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Field tmp(result._grid);
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coarseToFine(_coef._v[i],tmp);
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axpy(result,TensorRemove(innerProduct(tmp,src_orig)) / eval[i],tmp,result);
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}
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}
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template<typename CoarseField>
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void deflateCoarse(BasisFieldVector<CoarseField>& _coef,const std::vector<RealD>& eval,int N,const Field& src_orig,Field& result) {
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CoarseField src_coarse(_coef._v[0]._grid);
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CoarseField result_coarse = src_coarse;
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result_coarse = zero;
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fineToCoarse(src_orig,src_coarse);
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for (int i=0;i<N;i++) {
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axpy(result_coarse,TensorRemove(innerProduct(_coef._v[i],src_coarse)) / eval[i],_coef._v[i],result_coarse);
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}
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coarseToFine(result_coarse,result);
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}
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template<typename CoarseField>
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void deflate(BasisFieldVector<CoarseField>& _coef,const std::vector<RealD>& eval,int N,const Field& src_orig,Field& result) {
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// Deflation on coarse Grid is much faster, so use it by default. Deflation on fine Grid is kept for legacy reasons for now.
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deflateCoarse(_coef,eval,N,src_orig,result);
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}
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};
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}
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