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/* Ergo, version 3.8.2, a program for linear scaling electronic structure
* calculations.
* Copyright (C) 2023 Elias Rudberg, Emanuel H. Rubensson, Pawel Salek,
* and Anastasia Kruchinina.
*
* 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
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <http://www.gnu.org/licenses/>.
*
* Primary academic reference:
* Ergo: An open-source program for linear-scaling electronic structure
* calculations,
* Elias Rudberg, Emanuel H. Rubensson, Pawel Salek, and Anastasia
* Kruchinina,
* SoftwareX 7, 107 (2018),
* <http://dx.doi.org/10.1016/j.softx.2018.03.005>
*
* For further information about Ergo, see <http://www.ergoscf.org>.
*/
/** @file sparse_matrix.cc The implementation of sparse matrix optimized
for XC integration.
Notes: the atom reordering issues are not discussed. Some
preliminary experiments suggest that reordering may give 20%
speedup. The permutation speedup remain to be thoroughly tested.
*/
#include <string.h>
#include <list>
#include <map>
#include <set>
#include <vector>
#include <string.h>
#include "output.h"
#include "dft_common.h"
#include "sparse_matrix.h"
BEGIN_NAMESPACE(Dft)
/** computes a squared distance between two points. */
static inline ergo_real
sqDist(const ergo_real a[], const ergo_real b[])
{
ergo_real res = 0;
for(int i=0; i<3; i++) {
ergo_real d = a[i]-b[i];
res += d*d;
}
return res;
}
class NeighbourList {
const ShellSpecStruct* shellInfo;
std::list<int> neighbours;
ergo_real extent; /**< an approximation for the shell extent. */
public:
NeighbourList(const ShellSpecStruct* sis, ergo_real thr)
: shellInfo(sis), extent(0)
{
/* We should really check what is left out, an additional term
that is very relevant for functions with low exponent is
skipped. */
for(int i=0; i<sis->noOfContr; i++) {
ergo_real rad = template_blas_sqrt(-template_blas_log(thr/template_blas_fabs(sis->coeffList[i]))
/sis->exponentList[i]);
if (rad>extent)
extent = rad;
}
}
void setOverlappingWith(const std::vector<NeighbourList>& list) {
for(unsigned i=0; i < list.size(); ++i) {
const ShellSpecStruct& otherShell = *list[i].shellInfo;
ergo_real sqDistance = sqDist(shellInfo->centerCoords,
otherShell.centerCoords);
ergo_real minDist = list[i].extent + extent;
//printf("Comparing to shell # %i - %f away\n", i, sqrt(sqDistance));
if(sqDistance<minDist*minDist)
neighbours.push_back(i);
}
#if 0
printf("Radius %f . Found %d neighbours\n",
radius, neighbours.size());
#endif
}
std::list<int>::iterator begin() {
return neighbours.begin();
}
std::list<int>::iterator end() {
return neighbours.end();
}
size_t size() const {
return neighbours.size();
}
};
#if 0
static int
findExtremeShell(int noOfShells, const ShellSpecStruct* shellList)
{
static const ergo_real origin[] = { 0.0, 0.0, 0.0 };
ergo_real rMax = sqDist(shellList[0].centerCoords, origin);
int iMax = 0;
for(int i=1; i<noOfShells; i++) {
ergo_real r = sqDist(shellList[i].centerCoords, origin);
if (r>rMax) {
rMax = r;
iMax = i;
}
}
/* printf("Extreme Shell: %i\n", iMax); */
return iMax;
}
#endif
typedef ergo_real *ErgoRealPtr;
SparseMatrix::SparseMatrix(const SparsePattern& pattern_)
: pattern(pattern_), columns(new ErgoRealPtr[pattern_.size()]),
n(pattern_.size())
{
for(int col=0; col<n; col++) {
int colSize = pattern.getColumnSize(col);
columns[col] = new ergo_real[colSize];
for(int row=0; row<colSize; row++)
columns[col][row] = 0.0;
}
createOffsets(pattern);
}
SparseMatrix::SparseMatrix(const SparsePattern& pattern_,
const symmMatrix& sMat, const int *aoMap,
std::vector<int> const & permutationHML)
: pattern(pattern_), columns(new ErgoRealPtr[pattern_.size()]),
n(pattern_.size())
{
std::vector<int> rowI(n), colI(n);
for(int col=0; col<n; col++) {
int colSize = pattern.getColumnSize(col);
colI.clear();
rowI.clear();
columns[col] = new ergo_real[colSize];
const SparsePattern::Column& column = pattern[col];
SparsePattern::Column::Iterator colEnd = column.end();
for(SparsePattern::Column::Iterator row = column.begin();
row != colEnd; ++row) {
int pRow = aoMap[*row], pCol = aoMap[col];
if(col == 0)
if(pRow<pCol) {
int t = pRow; pRow = pCol; pCol = t;
}
rowI.push_back(pRow);
colI.push_back(pCol);
}
std::vector<ergo_real> columnsTmp;
sMat.get_values(rowI, colI, columnsTmp,
permutationHML, permutationHML);
/* FIXME: avoid slow copy somehow */
std::copy(columnsTmp.begin(), columnsTmp.end(),columns[col]);
#if 0
printf("get_values() for column %d returned:\n", col);
for(int row=0; row<colSize; row++)
printf("%d %d : %f\n", rowI[row], colI[row], columns[col][row]);
#endif
}
createOffsets(pattern);
//print("Densmat");
}
void
SparseMatrix::createOffsets(const SparsePattern& patt)
{
offsets = new int*[n];
his = new int*[n];
cnt = new int[n];
for(int col=0; col<n; col++) {
const SparsePattern::IntervalList& intervalList = patt[col].list;
int numberOfIntervals = intervalList.size();
int * off = offsets[col] = new int[numberOfIntervals];
int * hi = his[col] = new int[numberOfIntervals];
int offset = 0, last = 0, idx=0;
for(SparsePattern::IntervalList::const_iterator
i = intervalList.begin();
i != intervalList.end(); ++i) {
offset += i->lo - last;
off[idx] = offset;
hi[idx] = last = i->hi;
++idx;
}
cnt[col] = numberOfIntervals;
}
}
#if 1
void
SparseMatrix::print(const char *title) const
{
puts(title);
for(int row=0; row<n; row++) {
const SparsePattern::Column& col2 = pattern[row];
int prevCol = -1;
int offset = 0;
for(SparsePattern::Column::Iterator col = col2.begin();
col != col2.end(); ++col) {
/* Take care of skipped columns, if any. */
for(++prevCol; prevCol < *col; prevCol++) printf("********* ");
printf("%9.5f ", (double)columns[row][offset]);
offset++;
}
/* Complete tailing columns, if any. */
for(++prevCol; prevCol < n; prevCol++) printf("********* ");
puts("");
}
}
#endif
void
SparseMatrix::addSymmetrizedTo(symmMatrix& sMat, const int *aoMap,
std::vector<int> const & permutationHML) const
{
const unsigned BUF_SIZE = 10*n;
std::vector<int> rowI(BUF_SIZE), colI(BUF_SIZE);
std::vector<ergo_real> buf(BUF_SIZE);
colI.clear();
rowI.clear();
buf.clear();
for(int col=0; col<n; col++) {
const ergo_real *column = columns[col];
const SparsePattern::Column& patternCol = pattern[col];
int offset = 0;
SparsePattern::Column::Iterator colEnd = patternCol.end();
for(SparsePattern::Column::Iterator row= patternCol.begin();
row != colEnd; ++row) {
if(buf.size() == BUF_SIZE) {
sMat.add_values(rowI, colI, buf, permutationHML, permutationHML);
colI.clear();
rowI.clear();
buf.clear();
}
rowI.push_back(aoMap[*row]);
colI.push_back(aoMap[col]);
buf.push_back( column[offset]);
offset++;
}
}
if(!buf.empty())
sMat.add_values(rowI, colI, buf, permutationHML, permutationHML);
//print("XC mat");
}
END_NAMESPACE(Dft)
typedef ergo_real real;
static void
zeroorbs(real *tmp, const int *nblocks, const int (*iblocks)[2], int ldaib, int nvclen)
{
/* DIMENSION TMP(NVCLEN,NBAST),NBLOCKS(NSYM),IBLOCKS(2,LDAIB,NSYM) */
int ibl, idx, k;
for(ibl=0; ibl<nblocks[0]; ibl++)
for(idx=iblocks[ibl][0]; idx<iblocks[ibl][1]; idx++) {
real * tmpi = tmp + idx*nvclen;
for(k=0; k<nvclen; k++) tmpi[k] = 0.0;
}
}
void
getrho_blocked_lda(int nbast, const Dft::SparseMatrix& dmat,
const ergo_real * gao,
const int* nblocks, const int (*iblocks)[2],
int ldaib, ergo_real *tmp, int nvclen, ergo_real *rho)
{
/*
DIMENSION DMAT(NBAST,NBAST), GAO(NVCLEN,NBAST,*)
DIMENSION NBLOCKS(NSYM), IBLOCKS(2,LDAIB,NSYM), RHO(NVCLEN)
DIMENSION TMP(NVCLEN,NBAST)
*/
int colBl, col, rowBl, row, k;
real * tmpj, d;
zeroorbs(tmp, nblocks, iblocks, ldaib, nvclen);
for(colBl=0; colBl<nblocks[0]; colBl++)
for(col=iblocks[colBl][0]; col<iblocks[colBl][1]; col++) {
const real * gaoi = gao + col*nvclen;
for(rowBl=0; rowBl<nblocks[0]; rowBl++) {
int jtop = iblocks[rowBl][1] > col ? col : iblocks[rowBl][1];
for(row=iblocks[rowBl][0]; row<jtop; row++) {
d = dmat.at(row, col);
tmpj = tmp + row*nvclen;
for(int k=0; k<nvclen; k++)
tmpj[k] += gaoi[k]*d;
}
}
tmpj = tmp + col*nvclen;
d = dmat.at(col,col)*0.5;
for(k=0; k<nvclen; k++)
tmpj[k] += gaoi[k]*d;
}
memset(rho, 0, nvclen*sizeof(real));
for(colBl=0; colBl<nblocks[0]; colBl++)
for(col=iblocks[colBl][0]; col<iblocks[colBl][1]; col++) {
const real * gaoi = gao + col*nvclen;
const real * tmpi = tmp + col*nvclen;
for(k=0; k<nvclen; k++)
rho[k] += gaoi[k]*tmpi[k]*2;
}
}
void
getrho_blocked_gga(int nbast, const Dft::SparseMatrix& dmat,
const ergo_real * gao,
const int* nblocks, const int (*iblocks)[2],
int ldaib, ergo_real *tmp, int nvclen,
ergo_real *rho, ergo_real (*grad)[3])
{
/*
DIMENSION DMAT(NBAST,NBAST), GAO(NVCLEN,NBAST,*)
DIMENSION NBLOCKS(NSYM), IBLOCKS(2,LDAIB,NSYM), RHO(NVCLEN)
DIMENSION TMP(NVCLEN,NBAST*4)
*/
int colBl, col, rowBl, row, k;
real * tmpj, d;
zeroorbs(tmp, nblocks, iblocks, ldaib, nvclen);
for(colBl=0; colBl<nblocks[0]; colBl++)
for(col=iblocks[colBl][0]; col<iblocks[colBl][1]; col++) {
const real * gaoi = gao + col*nvclen;
for(rowBl=0; rowBl<nblocks[0]; rowBl++) {
for(row=iblocks[rowBl][0]; row<iblocks[rowBl][1]; row++) {
d = dmat.at(row, col);
tmpj = tmp + row*nvclen;
for(int k=0; k<nvclen; k++)
tmpj[k] += gaoi[k]*d;
}
}
}
memset(rho, 0, nvclen*sizeof(real));
memset(grad, 0, 3*nvclen*sizeof(real));
for(colBl=0; colBl<nblocks[0]; colBl++)
for(col=iblocks[colBl][0]; col<iblocks[colBl][1]; col++) {
const real * gaoi = gao + col*nvclen;
const real * tmpi = tmp + col*nvclen;
for(k=0; k<nvclen; k++) {
rho[k] += gaoi[k]*tmpi[k];
grad[k][0] += gaoi[k + nvclen*nbast ]*tmpi[k]*2;
grad[k][1] += gaoi[k + nvclen*nbast*2]*tmpi[k]*2;
grad[k][2] += gaoi[k + nvclen*nbast*3]*tmpi[k]*2;
}
}
}
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