206 lines
6.5 KiB
C++
206 lines
6.5 KiB
C++
/*
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* Copyright (C) 2007-2011 Dynare Team
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*
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* This file is part of Dynare.
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*
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* Dynare is free software: you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation, either version 3 of the License, or
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* (at your option) any later version.
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*
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* Dynare is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with Dynare. If not, see <http://www.gnu.org/licenses/>.
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*/
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/*
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* This mex file computes A*kron(B,C) or A*kron(B,B) without explicitly building kron(B,C) or kron(B,B), so that
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* one can consider large matrices A, B and/or C, and assuming that A is a the hessian of a dsge model
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* (dynare format). This mex file should not be used outside dr1.m.
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*/
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#include <string.h>
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#include <dynmex.h>
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#ifdef USE_OMP
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# include <omp.h>
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#endif
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#define DEBUG_OMP 0
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void
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sparse_hessian_times_B_kronecker_B(mwIndex *isparseA, mwIndex *jsparseA, double *vsparseA,
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double *B, double *D, mwSize mA, mwSize nA, mwSize mB, mwSize nB, int number_of_threads)
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{
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/*
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** Loop over the columns of kron(B,B) (or of the result matrix D).
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** This loop is splitted into two nested loops because we use the
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** symmetric pattern of the hessian matrix.
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*/
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#if USE_OMP
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# pragma omp parallel for num_threads(number_of_threads)
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#endif
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for (mwIndex j1B = 0; j1B < nB; j1B++)
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{
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#if DEBUG_OMP
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mexPrintf("%d thread number is %d (%d).\n", j1B, omp_get_thread_num(), omp_get_num_threads());
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#endif
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for (mwIndex j2B = j1B; j2B < nB; j2B++)
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{
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mwIndex jj = j1B*nB+j2B; // column of kron(B,B) index.
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mwIndex iv = 0;
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int nz_in_column_ii_of_A = 0;
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mwIndex k1 = 0;
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mwIndex k2 = 0;
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/*
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** Loop over the rows of kron(B,B) (column jj).
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*/
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for (mwIndex ii = 0; ii < nA; ii++)
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{
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k1 = jsparseA[ii];
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k2 = jsparseA[ii+1];
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if (k1 < k2) // otherwise column ii of A does not have non zero elements (and there is nothing to compute).
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{
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++nz_in_column_ii_of_A;
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mwIndex i1B = (ii/mB);
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mwIndex i2B = (ii%mB);
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double bb = B[j1B*mB+i1B]*B[j2B*mB+i2B];
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/*
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** Loop over the non zero entries of A(:,ii).
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*/
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for (mwIndex k = k1; k < k2; k++)
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{
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mwIndex kk = isparseA[k];
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D[jj*mA+kk] = D[jj*mA+kk] + bb*vsparseA[iv];
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iv++;
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}
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}
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}
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if (nz_in_column_ii_of_A > 0)
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{
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memcpy(&D[(j2B*nB+j1B)*mA], &D[jj*mA], mA*sizeof(double));
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}
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}
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}
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}
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void
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sparse_hessian_times_B_kronecker_C(mwIndex *isparseA, mwIndex *jsparseA, double *vsparseA,
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double *B, double *C, double *D,
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mwSize mA, mwSize nA, mwSize mB, mwSize nB, mwSize mC, mwSize nC, int number_of_threads)
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{
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/*
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** Loop over the columns of kron(B,B) (or of the result matrix D).
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*/
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#if USE_OMP
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# pragma omp parallel for num_threads(number_of_threads)
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#endif
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for (mwIndex jj = 0; jj < nB*nC; jj++) // column of kron(B,C) index.
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{
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// Uncomment the following line to check if all processors are used.
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#if DEBUG_OMP
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mexPrintf("%d thread number is %d (%d).\n", jj, omp_get_thread_num(), omp_get_num_threads());
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#endif
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mwIndex jB = jj/nC;
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mwIndex jC = jj%nC;
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mwIndex k1 = 0;
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mwIndex k2 = 0;
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mwIndex iv = 0;
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int nz_in_column_ii_of_A = 0;
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/*
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** Loop over the rows of kron(B,C) (column jj).
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*/
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for (mwIndex ii = 0; ii < nA; ii++)
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{
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k1 = jsparseA[ii];
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k2 = jsparseA[ii+1];
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if (k1 < k2) // otherwise column ii of A does not have non zero elements (and there is nothing to compute).
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{
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++nz_in_column_ii_of_A;
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mwIndex iC = (ii%mB);
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mwIndex iB = (ii/mB);
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double cb = C[jC*mC+iC]*B[jB*mB+iB];
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/*
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** Loop over the non zero entries of A(:,ii).
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*/
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for (mwIndex k = k1; k < k2; k++)
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{
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mwIndex kk = isparseA[k];
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D[jj*mA+kk] = D[jj*mA+kk] + cb*vsparseA[iv];
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iv++;
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}
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}
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}
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}
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}
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void
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mexFunction(int nlhs, mxArray *plhs[], int nrhs, const mxArray *prhs[])
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{
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// Check input and output:
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if ((nrhs > 4) || (nrhs < 3) )
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DYN_MEX_FUNC_ERR_MSG_TXT("sparse_hessian_times_B_kronecker_C takes 3 or 4 input arguments and provides 2 output arguments.");
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if (!mxIsSparse(prhs[0]))
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DYN_MEX_FUNC_ERR_MSG_TXT("sparse_hessian_times_B_kronecker_C: First input must be a sparse (dynare) hessian matrix.");
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// Get & Check dimensions (columns and rows):
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mwSize mA, nA, mB, nB, mC, nC;
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mA = mxGetM(prhs[0]);
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nA = mxGetN(prhs[0]);
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mB = mxGetM(prhs[1]);
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nB = mxGetN(prhs[1]);
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if (nrhs == 4) // A*kron(B,C) is to be computed.
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{
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mC = mxGetM(prhs[2]);
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nC = mxGetN(prhs[2]);
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if (mB*mC != nA)
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DYN_MEX_FUNC_ERR_MSG_TXT("Input dimension error!");
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}
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else // A*kron(B,B) is to be computed.
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{
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if (mB*mB != nA)
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DYN_MEX_FUNC_ERR_MSG_TXT("Input dimension error!");
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}
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// Get input matrices:
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double *B, *C;
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int numthreads;
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B = mxGetPr(prhs[1]);
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numthreads = (int) mxGetScalar(prhs[2]);
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if (nrhs == 4)
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{
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C = mxGetPr(prhs[2]);
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numthreads = (int) mxGetScalar(prhs[3]);
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}
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// Sparse (dynare) hessian matrix.
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mwIndex *isparseA = (mwIndex *) mxGetIr(prhs[0]);
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mwIndex *jsparseA = (mwIndex *) mxGetJc(prhs[0]);
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double *vsparseA = mxGetPr(prhs[0]);
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// Initialization of the ouput:
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double *D;
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if (nrhs == 4)
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{
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plhs[0] = mxCreateDoubleMatrix(mA, nB*nC, mxREAL);
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}
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else
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{
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plhs[0] = mxCreateDoubleMatrix(mA, nB*nB, mxREAL);
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}
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D = mxGetPr(plhs[0]);
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// Computational part:
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if (nrhs == 3)
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{
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sparse_hessian_times_B_kronecker_B(isparseA, jsparseA, vsparseA, B, D, mA, nA, mB, nB, numthreads);
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}
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else
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{
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sparse_hessian_times_B_kronecker_C(isparseA, jsparseA, vsparseA, B, C, D, mA, nA, mB, nB, mC, nC, numthreads);
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}
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plhs[1] = mxCreateDoubleScalar(0);
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}
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