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Grid/lib/algorithms/iterative/BlockImplicitlyRestartedLanczos/FieldBasisVector.h

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2017-10-10 14:15:11 +01:00
namespace Grid {
template<class Field>
class BasisFieldVector {
public:
int _Nm;
typedef typename Field::scalar_type Coeff_t;
typedef typename Field::vector_type vCoeff_t;
typedef typename Field::vector_object vobj;
typedef typename vobj::scalar_object sobj;
std::vector<Field> _v; // _Nfull vectors
void report(int n,GridBase* value) {
std::cout << GridLogMessage << "BasisFieldVector allocated:\n";
std::cout << GridLogMessage << " Delta N = " << n << "\n";
std::cout << GridLogMessage << " Size of full vectors (size) = " <<
((double)n*sizeof(vobj)*value->oSites() / 1024./1024./1024.) << " GB\n";
std::cout << GridLogMessage << " Size = " << _v.size() << " Capacity = " << _v.capacity() << std::endl;
value->Barrier();
if (value->IsBoss()) {
system("cat /proc/meminfo");
}
value->Barrier();
}
BasisFieldVector(int Nm,GridBase* value) : _Nm(Nm), _v(Nm,value) {
report(Nm,value);
}
~BasisFieldVector() {
}
Field& operator[](int i) {
return _v[i];
}
void orthogonalize(Field& w, int k) {
for(int j=0; j<k; ++j){
Coeff_t ip = (Coeff_t)innerProduct(_v[j],w);
w = w - ip*_v[j];
}
}
void rotate(std::vector<RealD>& Qt,int j0, int j1, int k0,int k1,int Nm) {
GridBase* grid = _v[0]._grid;
#pragma omp parallel
{
std::vector < vobj > B(Nm);
#pragma omp for
for(int ss=0;ss < grid->oSites();ss++){
for(int j=j0; j<j1; ++j) B[j]=0.;
for(int j=j0; j<j1; ++j){
for(int k=k0; k<k1; ++k){
B[j] +=Qt[k+Nm*j] * _v[k]._odata[ss];
}
}
for(int j=j0; j<j1; ++j){
_v[j]._odata[ss] = B[j];
}
}
}
}
size_t size() const {
return _Nm;
}
void resize(int n) {
if (n > _Nm)
_v.reserve(n);
_v.resize(n,_v[0]._grid);
if (n < _Nm)
_v.shrink_to_fit();
report(n - _Nm,_v[0]._grid);
_Nm = n;
}
std::vector<int> getIndex(std::vector<RealD>& sort_vals) {
std::vector<int> idx(sort_vals.size());
iota(idx.begin(), idx.end(), 0);
// sort indexes based on comparing values in v
sort(idx.begin(), idx.end(),
[&sort_vals](int i1, int i2) {return ::fabs(sort_vals[i1]) < ::fabs(sort_vals[i2]);});
return idx;
}
void reorderInPlace(std::vector<RealD>& sort_vals, std::vector<int>& idx) {
GridStopWatch gsw;
gsw.Start();
int nswaps = 0;
for (size_t i=0;i<idx.size();i++) {
if (idx[i] != i) {
// find proper place (this could be done in logarithmic time, don't bother for now)
size_t j;
for (j=i;j<idx.size();j++)
if (idx[j]==i)
break;
assert(j!=idx.size());
Field _t(_v[0]._grid);
_t = _v[idx[j]];
_v[idx[j]] = _v[idx[i]];
_v[idx[i]] = _t;
RealD _td = sort_vals[idx[j]];
sort_vals[idx[j]] = sort_vals[idx[i]];
sort_vals[idx[i]] = _td;
int _tt = idx[i];
idx[i] = idx[j];
idx[j] = _tt;
nswaps++;
}
}
// sort values
gsw.Stop();
std::cout << GridLogMessage << "Sorted eigenspace in place in " << gsw.Elapsed() << " using " << nswaps << " swaps" << std::endl;
}
void sortInPlace(std::vector<RealD>& sort_vals, bool reverse) {
std::vector<int> idx = getIndex(sort_vals);
if (reverse)
std::reverse(idx.begin(), idx.end());
reorderInPlace(sort_vals,idx);
}
void deflate(const std::vector<RealD>& eval,const Field& src_orig,Field& result) {
result = zero;
int N = (int)_v.size();
for (int i=0;i<N;i++) {
Field& tmp = _v[i];
axpy(result,TensorRemove(innerProduct(tmp,src_orig)) / eval[i],tmp,result);
}
}
};
}