Beispiel #1
0
int SOLVE_CHOL_ONE(MATRIX_T L, VECTOR_T B)
{

  /* solves Ax = B where A = LL^T */

  int info;
  int N = (int)L.nrows;
  int Nrhs = (int)1;
  char uplo = 'L';

  POTRS(&uplo,&N,&Nrhs,L.m,&N,B.v,&N,&info);

  return info;

}
Beispiel #2
0
int SOLVE_CHOL_MULTIPLE(MATRIX_T L, MATRIX_T B)
{

  /* solves Ax = B where A = LL^T */

  int info;
  int N = (int)L.nrows;
  int Nrhs = (int)B.ncols;
  char uplo = 'L';

  POTRS(&uplo,&N,&Nrhs,L.m,&N,B.m,&N,&info);

  return info;

}
Beispiel #3
0
//---------------------------------------------------------
DVec& chol_solve(const DMat& ch, const DVec& b)
//---------------------------------------------------------
{
  // Solves a linear system using Cholesky-factored 
  // symmetric positive-definite matrix, A = U^T U.

  if (FACT_CHOL != ch.get_factmode()) {umERROR("chol_solve(ch,b)", "matrix is not factored.");}
  int M=ch.num_rows(), lda=ch.num_rows(); 
  int nrhs=1, ldb=b.size();   assert(ldb == M);
  char uplo = 'U';  int info=0; 
  double* ch_data = const_cast<double*>(ch.data());

  // copy RHS into x, then overwrite x with solution
  DVec* x = new DVec(b, OBJ_temp);
  POTRS (uplo, M, nrhs, ch_data, lda, x->data(), ldb, info);
  if (info) { umERROR("chol_solve(ch,b)", "dpotrs reports: info = %d", info); }
  return (*x);
}
Beispiel #4
0
//---------------------------------------------------------
bool chol_solve(const DMat& ch, const DMat& B, DMat& X)
//---------------------------------------------------------
{
  // Solve a set of linear systems using Cholesky-factored 
  // symmetric positive-definite matrix, A = U^T U.

  if (FACT_CHOL != ch.get_factmode()) {umERROR("chol_solve(ch,B,X)", "matrix is not factored.");}
  int M =ch.num_rows(), lda=ch.num_rows(); 
  int ldb=B.num_rows(), nrhs=B.num_cols(); assert(ldb == M);
  char uplo = 'U';  int info=0; 
  double* ch_data = const_cast<double*>(ch.data());

  X = B;  // overwrite X with RHS's, then solutions
  POTRS (uplo, M, nrhs, ch_data, lda, X.data(), ldb, info);

  if (info) { umERROR("chol_solve(ch,B,X)", "dpotrs reports: info = %d", info); }
  return true;
}
Beispiel #5
0
int main(int argc, char *argv[]){

#ifndef COMPLEX
  char *trans[] = {"T", "N"};
#else
  char *trans[] = {"C", "N"};
#endif
  char *uplo[]  = {"U", "L"};
  FLOAT alpha[] = {1.0, 0.0};
  FLOAT beta [] = {0.0, 0.0};

  FLOAT *a, *b;

  char *p;
  char btest = 'F';

  blasint m, i, j, info, uplos=0;
  double flops;

  int from =   1;
  int to   = 200;
  int step =   1;

  struct timeval start, stop;
  double time1;

  argc--;argv++;

  if (argc > 0) { from     = atol(*argv);		argc--; argv++;}
  if (argc > 0) { to       = MAX(atol(*argv), from);	argc--; argv++;}
  if (argc > 0) { step     = atol(*argv);		argc--; argv++;}

  if ((p = getenv("OPENBLAS_UPLO")))
	if (*p == 'L') uplos=1;

  if ((p = getenv("OPENBLAS_TEST"))) btest=*p;

  fprintf(stderr, "From : %3d  To : %3d Step = %3d Uplo = %c\n", from, to, step,*uplo[uplos]);

  if (( a    = (FLOAT *)malloc(sizeof(FLOAT) * to * to * COMPSIZE)) == NULL){
    fprintf(stderr,"Out of Memory!!\n");exit(1);
  }

  if (( b    = (FLOAT *)malloc(sizeof(FLOAT) * to * to * COMPSIZE)) == NULL){
    fprintf(stderr,"Out of Memory!!\n");exit(1);
  }

  for(m = from; m <= to; m += step){

#ifndef COMPLEX
      if (uplos & 1) {
	for (j = 0; j < m; j++) {
	  for(i = 0; i < j; i++)     a[i + j * m] = 0.;
	                             a[j + j * m] = ((double) rand() / (double) RAND_MAX) + 8.;
	  for(i = j + 1; i < m; i++) a[i + j * m] = ((double) rand() / (double) RAND_MAX) - 0.5;
	}
      } else {
	for (j = 0; j < m; j++) {
	  for(i = 0; i < j; i++)     a[i + j * m] = ((double) rand() / (double) RAND_MAX) - 0.5;
	                             a[j + j * m] = ((double) rand() / (double) RAND_MAX) + 8.;
	  for(i = j + 1; i < m; i++) a[i + j * m] = 0.;
	}
      }
#else
      if (uplos & 1) {
	for (j = 0; j < m; j++) {
	  for(i = 0; i < j; i++) {
	    a[(i + j * m) * 2 + 0] = 0.;
	    a[(i + j * m) * 2 + 1] = 0.;
	  }

	  a[(j + j * m) * 2 + 0] = ((double) rand() / (double) RAND_MAX) + 8.;
	  a[(j + j * m) * 2 + 1] = 0.;

	  for(i = j + 1; i < m; i++) {
	    a[(i + j * m) * 2 + 0] = ((double) rand() / (double) RAND_MAX) - 0.5;
	    a[(i + j * m) * 2 + 1] = ((double) rand() / (double) RAND_MAX) - 0.5;
	  }
	}
      } else {
	for (j = 0; j < m; j++) {
	  for(i = 0; i < j; i++) {
	    a[(i + j * m) * 2 + 0] = ((double) rand() / (double) RAND_MAX) - 0.5;
	    a[(i + j * m) * 2 + 1] = ((double) rand() / (double) RAND_MAX) - 0.5;
	  }

	  a[(j + j * m) * 2 + 0] = ((double) rand() / (double) RAND_MAX) + 8.;
	  a[(j + j * m) * 2 + 1] = 0.;

	  for(i = j + 1; i < m; i++) {
	    a[(i + j * m) * 2 + 0] = 0.;
	    a[(i + j * m) * 2 + 1] = 0.;
	  }
	}
      }
#endif

      SYRK(uplo[uplos], trans[uplos], &m, &m, alpha, a, &m, beta, b, &m);

      gettimeofday( &start, (struct timezone *)0);

      POTRF(uplo[uplos], &m, b, &m, &info);

      gettimeofday( &stop, (struct timezone *)0);

      if (info != 0) {
	fprintf(stderr, "Potrf info = %d\n", info);
	exit(1);
      }

      time1 = (double)(stop.tv_sec - start.tv_sec) + (double)((stop.tv_usec - start.tv_usec)) * 1.e-6;
      flops = COMPSIZE * COMPSIZE * (1.0/3.0 * (double)m * (double)m *(double)m +1.0/2.0* (double)m *(double)m + 1.0/6.0* (double)m) / time1 * 1.e-6;

      if ( btest == 'S' )
      {
	
 	for(j = 0; j < to; j++){
      		for(i = 0; i < to * COMPSIZE; i++){
        		a[i + j * to * COMPSIZE] = ((FLOAT) rand() / (FLOAT) RAND_MAX) - 0.5;
      		}
    	}

      	gettimeofday( &start, (struct timezone *)0);

      	POTRS(uplo[uplos], &m, &m, b, &m, a, &m,  &info);

      	gettimeofday( &stop, (struct timezone *)0);

      	if (info != 0) {
		fprintf(stderr, "Potrs info = %d\n", info);
		exit(1);
        }
        time1 = (double)(stop.tv_sec - start.tv_sec) + (double)((stop.tv_usec - start.tv_usec)) * 1.e-6;
        flops = COMPSIZE * COMPSIZE * (2.0 * (double)m * (double)m *(double)m ) / time1 * 1.e-6;

      }
	
      if ( btest == 'I' )
      {
	
      	gettimeofday( &start, (struct timezone *)0);

      	POTRI(uplo[uplos], &m, b, &m, &info);

      	gettimeofday( &stop, (struct timezone *)0);

      	if (info != 0) {
		fprintf(stderr, "Potri info = %d\n", info);
		exit(1);
        }

        time1 = (double)(stop.tv_sec - start.tv_sec) + (double)((stop.tv_usec - start.tv_usec)) * 1.e-6;
        flops = COMPSIZE * COMPSIZE * (2.0/3.0 * (double)m * (double)m *(double)m +1.0/2.0* (double)m *(double)m + 5.0/6.0* (double)m) / time1 * 1.e-6;
      }
	
      fprintf(stderr, "%8d : %10.2f MFlops : %10.3f Sec : Test=%c\n",m,flops ,time1,btest);


  }


  return 0;
}
/*
 * This function returns the solution of Ax=b
 *
 * The function assumes that A is symmetric & postive definite and employs
 * the Cholesky decomposition:
 * If A=L L^T with L lower triangular, the system to be solved becomes
 * (L L^T) x = b
 * This amounts to solving L y = b for y and then L^T x = y for x
 *
 * A is mxm, b is mx1
 *
 * The function returns 0 in case of error, 1 if successful
 *
 * This function is often called repetitively to solve problems of identical
 * dimensions. To avoid repetitive malloc's and free's, allocated memory is
 * retained between calls and free'd-malloc'ed when not of the appropriate size.
 * A call with NULL as the first argument forces this memory to be released.
 */
int AX_EQ_B_CHOL(LM_REAL *A, LM_REAL *B, LM_REAL *x, int m)
{
__STATIC__ LM_REAL *buf=NULL;
__STATIC__ int buf_sz=0;

LM_REAL *a;
int a_sz, tot_sz;
int info, nrhs=1;
   
    if(!A)
#ifdef LINSOLVERS_RETAIN_MEMORY
    {
      if(buf) free(buf);
      buf=NULL;
      buf_sz=0;

      return 1;
    }
#else
      return 1; /* NOP */
#endif /* LINSOLVERS_RETAIN_MEMORY */
   
    /* calculate required memory size */
    a_sz=m*m;
    tot_sz=a_sz;

#ifdef LINSOLVERS_RETAIN_MEMORY
    if(tot_sz>buf_sz){ /* insufficient memory, allocate a "big" memory chunk at once */
      if(buf) free(buf); /* free previously allocated memory */

      buf_sz=tot_sz;
      buf=(LM_REAL *)malloc(buf_sz*sizeof(LM_REAL));
      if(!buf){
        fprintf(stderr, RCAT("memory allocation in ", AX_EQ_B_CHOL) "() failed!\n");
        exit(1);
      }
    }
#else
      buf_sz=tot_sz;
      buf=(LM_REAL *)malloc(buf_sz*sizeof(LM_REAL));
      if(!buf){
        fprintf(stderr, RCAT("memory allocation in ", AX_EQ_B_CHOL) "() failed!\n");
        exit(1);
      }
#endif /* LINSOLVERS_RETAIN_MEMORY */

  a=buf;

  /* store A into a and B into x. A is assumed symmetric,
   * hence no transposition is needed
   */
  memcpy(a, A, a_sz*sizeof(LM_REAL));
  memcpy(x, B, m*sizeof(LM_REAL));

  /* Cholesky decomposition of A */
  //POTF2("L", (int *)&m, a, (int *)&m, (int *)&info);
  POTRF("L", (int *)&m, a, (int *)&m, (int *)&info);
  /* error treatment */
  if(info!=0){
    if(info<0){
      fprintf(stderr, RCAT(RCAT(RCAT("LAPACK error: illegal value for argument %d of ", POTF2) "/", POTRF) " in ",
                      AX_EQ_B_CHOL) "()\n", -info);
      exit(1);
    }
    else{
      fprintf(stderr, RCAT(RCAT(RCAT("LAPACK error: the leading minor of order %d is not positive definite,\nthe factorization could not be completed for ", POTF2) "/", POTRF) " in ", AX_EQ_B_CHOL) "()\n", info);
#ifndef LINSOLVERS_RETAIN_MEMORY
      free(buf);
#endif

      return 0;
    }
  }

  /* solve using the computed Cholesky in one lapack call */
  POTRS("L", (int *)&m, (int *)&nrhs, a, (int *)&m, x, (int *)&m, &info);
  if(info<0){
    fprintf(stderr, RCAT(RCAT("LAPACK error: illegal value for argument %d of ", POTRS) " in ", AX_EQ_B_CHOL) "()\n", -info);
    exit(1);
  }

#if 0
  /* alternative: solve the linear system L y = b ... */
  TRTRS("L", "N", "N", (int *)&m, (int *)&nrhs, a, (int *)&m, x, (int *)&m, &info);
  /* error treatment */
  if(info!=0){
    if(info<0){
      fprintf(stderr, RCAT(RCAT("LAPACK error: illegal value for argument %d of ", TRTRS) " in ", AX_EQ_B_CHOL) "()\n", -info);
      exit(1);
    }
    else{
      fprintf(stderr, RCAT("LAPACK error: the %d-th diagonal element of A is zero (singular matrix) in ", AX_EQ_B_CHOL) "()\n", info);
#ifndef LINSOLVERS_RETAIN_MEMORY
      free(buf);
#endif

      return 0;
    }
  }

  /* ... solve the linear system L^T x = y */
  TRTRS("L", "T", "N", (int *)&m, (int *)&nrhs, a, (int *)&m, x, (int *)&m, &info);
  /* error treatment */
  if(info!=0){
    if(info<0){
      fprintf(stderr, RCAT(RCAT("LAPACK error: illegal value for argument %d of ", TRTRS) "in ", AX_EQ_B_CHOL) "()\n", -info);
      exit(1);
    }
    else{
      fprintf(stderr, RCAT("LAPACK error: the %d-th diagonal element of A is zero (singular matrix) in ", AX_EQ_B_CHOL) "()\n", info);
#ifndef LINSOLVERS_RETAIN_MEMORY
      free(buf);
#endif

      return 0;
    }
  }
#endif /* 0 */

#ifndef LINSOLVERS_RETAIN_MEMORY
  free(buf);
#endif

	return 1;
}
void l2ls_learn_basis_dual(DOUBLE *Dopt, DOUBLE *Dorig, DOUBLE *X, DOUBLE *S, DOUBLE l2norm, INT length, INT N, INT K, INT numSamples) {

	DOUBLE *SSt = (DOUBLE *) MALLOC(K * K * sizeof(DOUBLE));
	
	CHAR uplo = 'U';
	CHAR trans = 'N';
	INT SYRKN = K;
	INT SYRKK = numSamples;
	DOUBLE alpha = 1;
	INT SYRKLDA = K;
	DOUBLE beta = 0;
	INT SYRKLDC = K;
	
	SYRK(&uplo, &trans, &SYRKN, &SYRKK, &alpha, S, &SYRKLDA, &beta, SSt, &SYRKLDC);
	
	DOUBLE *XSt = (DOUBLE *) MALLOC(N * K * sizeof(DOUBLE));

	CHAR transa = 'N';
	CHAR transb = 'T';
	INT GEMMM = N;
	INT GEMMN = K;
	INT GEMMK = numSamples;
	alpha = 1;
	INT GEMMLDA = N;
	INT GEMMLDB = K;
	beta = 0;
	INT GEMMLDC = N;
	
	GEMM(&transa, &transb, &GEMMM, &GEMMN, &GEMMK, &alpha, X, &GEMMLDA, S, &GEMMLDB, &beta, XSt, &GEMMLDC);
	DOUBLE *SXt = (DOUBLE *) MALLOC(N * K * sizeof(DOUBLE));
	transpose(XSt, SXt, N, K);
	
	INT iterK;	
	DOUBLE *dualLambdaOrig = (DOUBLE *) MALLOC(K * sizeof(DOUBLE));
	if (Dorig == NULL) {
		srand(time(NULL));
		for (iterK = 0; iterK < K; ++iterK) {
			dualLambdaOrig[iterK] = 10 * (DOUBLE) rand() / (DOUBLE) RAND_MAX;
		}
	} else {
		
		INT maxNK = IMAX(N, K);
		DOUBLE *B = (DOUBLE *) MALLOC(maxNK * maxNK * sizeof(DOUBLE));
		for (iterK = 0; iterK < K; ++iterK) {
			datacpy(&B[iterK * maxNK], &XSt[iterK * N], K);
		}
		
		INT GELSYM = N;
		INT GELSYN = K;
		INT GELSYNRHS = K;
		INT GELSYLDA = N;
		INT GELSYLDB = maxNK;
		INT *jpvt = (INT *) MALLOC(K * sizeof(INT));
		DOUBLE rcond;
		INT rank;
		INT lwork = -1;
		DOUBLE work_temp;
		DOUBLE *work;
		INT INFO;

		GELSY(&GELSYM, &GELSYN, &GELSYNRHS, Dorig, &GELSYLDA, B, &GELSYLDB, jpvt, &rcond, &rank, &work_temp, &lwork, &INFO);
		
		lwork = (INT) work_temp;
		work = (DOUBLE*) MALLOC(lwork * sizeof(DOUBLE));

		
		GELSY(&GELSYM, &GELSYN, &GELSYNRHS, Dorig, &GELSYLDA, XSt, &GELSYLDB, jpvt, &rcond, &rank, work, &lwork, &INFO);

		for (iterK = 0; iterK < K; ++iterK) {
			dualLambdaOrig[K] = B[iterK * K + iterK] - SSt[iterK * K + iterK];
		}
		
		FREE(work);
		FREE(B);
		FREE(jpvt);
	}

	DOUBLE *SXtXSt = (DOUBLE *) MALLOC(K * K * sizeof(DOUBLE));
	
	uplo = 'U';
	trans = 'N';
	SYRKN = K;
	SYRKK = N;
	alpha = 1;
	SYRKLDA = K;
	beta = 0;
	SYRKLDC = K;
	
	SYRK(&uplo, &trans, &SYRKN, &SYRKK, &alpha, SXt, &SYRKLDA, &beta, SXtXSt, &SYRKLDC);

	DOUBLE c = SQR(l2norm);

	CHAR norm = 'F';
	INT LANGEM = N;
	INT LANGEN = numSamples;
	INT LANGELDA = N;
	
	DOUBLE trXXt = LANGE(&norm, &LANGEM, &LANGEN, X, &LANGELDA, NULL);
	trXXt = SQR(trXXt);
	
/*
	DOUBLE *dualLambdaOpt = (DOUBLE *) MALLOC(K * sizeof(DOUBLE));
*/
	DOUBLE *dualLambdaOpt = XSt;
	minimize_dual(dualLambdaOpt, dualLambdaOrig, length, SSt, SXt, SXtXSt, trXXt, c, N, K);

	for (iterK = 0; iterK < K; ++iterK) {
		SSt[iterK * K + iterK] += dualLambdaOpt[iterK];
	}

	uplo = 'U';
	INT POTRSN = K;
	INT POTRSLDA = K;
	INT INFO;
	POTRF(&uplo, &POTRSN, SSt, &POTRSLDA, &INFO);
	
	INT POTRSNRHS = N;
	INT POTRSLDB = K;
	
	POTRS(&uplo, &POTRSN, &POTRSNRHS, SSt, &POTRSLDA, SXt, &POTRSLDB, &INFO);

	transpose(SXt, Dopt, K, N);
	
	FREE(SSt);
	FREE(XSt);
	FREE(SXt);
	FREE(dualLambdaOrig);
	FREE(SXtXSt);
}
void dual_obj_grad(DOUBLE *obj, DOUBLE *deriv, DOUBLE *dualLambda, DOUBLE *SSt, DOUBLE *SXt, DOUBLE *SXtXSt, DOUBLE trXXt, \
					DOUBLE c, INT N, INT K, INT derivFlag, DOUBLE *SStLambda, DOUBLE *tempMatrix) {
	
	INT maxNK = IMAX(N, K);
	INT SStLambdaFlag = 0;
	if (SStLambda == NULL) { 
		SStLambda = (DOUBLE *) MALLOC(maxNK * K * sizeof(DOUBLE));
		SStLambdaFlag = 1;
	}

	INT tempMatrixFlag = 0;
	if (tempMatrix == NULL) { 
		tempMatrix = (DOUBLE *) MALLOC(maxNK * K * sizeof(DOUBLE));
		tempMatrixFlag = 1;
	}
	
	datacpy(SStLambda, SSt, K * K);
	
	INT iterK;
	
/*
	#pragma omp parallel for private(iterK) shared(SStLambda, dualLambda, K)
*/
	for (iterK = 0; iterK < K; ++iterK) {
		SStLambda[iterK * K + iterK] += dualLambda[iterK];
	}
	
	CHAR uplo = 'U';
	INT POTRSN = K;
	INT POTRSLDA = K;
	INT INFO;
	
	POTRF(&uplo, &POTRSN, SStLambda, &POTRSLDA, &INFO);
	
	datacpy(tempMatrix, SXtXSt, K * K);
	
	INT POTRSNRHS = K;
	INT POTRSLDB = K;
	
	POTRS(&uplo, &POTRSN, &POTRSNRHS, SStLambda, &POTRSLDA, tempMatrix, &POTRSLDB, &INFO);

	DOUBLE objTemp = 0;
	
/*
	#pragma omp parallel for private(iterK) shared(tempMatrix, K) reduction(-: objTemp)
*/
	for (iterK = 0; iterK < K; ++iterK) {
		objTemp = objTemp - tempMatrix[iterK * K + iterK];
	}
	
	INT ASUMN = K;
	INT incx = 1;
	DOUBLE sumDualLambda = ASUM(&ASUMN, dualLambda, &incx);
	
	objTemp += trXXt - c * sumDualLambda;
	*obj = - objTemp;

	if (derivFlag == 1) {
		
		datacpy(tempMatrix, SXt, K * N);
		
		POTRSNRHS = N;
		POTRSLDB = K;
	
		POTRS(&uplo, &POTRSN, &POTRSNRHS, SStLambda, &POTRSLDA, tempMatrix, &POTRSLDB, &INFO);
		
		transpose(tempMatrix, SStLambda, K, N);
		
		INT NRM2N = N;
		DOUBLE tempNorm;
		#pragma omp parallel for private(iterK, tempNorm) shared(SStLambda, deriv, K, c)
		for (iterK = 0; iterK < K; ++iterK) {
			tempNorm = NRM2(&NRM2N, &SStLambda[iterK * N], &incx);
			deriv[iterK] = - SQR(tempNorm) + c;
		}
	}
	
	if (SStLambdaFlag == 1) {
		FREE(SStLambda);
	}
	
	if (tempMatrixFlag == 1) {
		FREE(tempMatrix);
	}
}
//=============================================================================
int Epetra_SerialSpdDenseSolver::Solve(void) {
  int ierr = 0;

  // We will call one of four routines depending on what services the user wants and 
  // whether or not the matrix has been inverted or factored already.
  //
  // If the matrix has been inverted, use DGEMM to compute solution.
  // Otherwise, if the user want the matrix to be equilibrated or wants a refined solution, we will
  // call the X interface.
  // Otherwise, if the matrix is already factored we will call the TRS interface.
  // Otherwise, if the matrix is unfactored we will call the SV interface.

  if (Equilibrate_) {
    ierr = Epetra_SerialDenseSolver::EquilibrateRHS();
    B_Equilibrated_ = true;
  }
  EPETRA_CHK_ERR(ierr);
  if (A_Equilibrated_ && !B_Equilibrated_) EPETRA_CHK_ERR(-1); // Matrix and vectors must be similarly scaled
  if (!A_Equilibrated_ && B_Equilibrated_) EPETRA_CHK_ERR(-2);
  if (B_==0) EPETRA_CHK_ERR(-3); // No B
  if (X_==0) EPETRA_CHK_ERR(-4); // No B

  if (ShouldEquilibrate() && !A_Equilibrated_) ierr = 1; // Warn that the system should be equilibrated.

  double DN = N_;
  double DNRHS = NRHS_;
  if (Inverted()) {

    if (B_==X_) EPETRA_CHK_ERR(-100); // B and X must be different for this case
    GEMM('N', 'N', N_, NRHS_, N_, 1.0, AF_, LDAF_,
		B_, LDB_, 0.0, X_, LDX_);
    if (INFO_!=0) EPETRA_CHK_ERR(INFO_);
    UpdateFlops(2.0*DN*DN*DNRHS);
    Solved_ = true;
  }
  else {

    if (!Factored()) Factor(); // Matrix must be factored
    if (B_!=X_) {
       *LHS_ = *RHS_; // Copy B to X if needed 
       X_ = LHS_->A(); LDX_ = LHS_->LDA();
    }
    
    POTRS(SymMatrix_->UPLO(), N_, NRHS_, AF_, LDAF_, X_, LDX_, &INFO_);
    if (INFO_!=0) EPETRA_CHK_ERR(INFO_);
    UpdateFlops(2.0*DN*DN*DNRHS);
    Solved_ = true;

  }
  int ierr1=0;
  if (RefineSolution_) ierr1 = ApplyRefinement();
  if (ierr1!=0) {
    EPETRA_CHK_ERR(ierr1);
  }
  else {
    EPETRA_CHK_ERR(ierr);
  }
  if (Equilibrate_) ierr1 = Epetra_SerialDenseSolver::UnequilibrateLHS();
  EPETRA_CHK_ERR(ierr1);
  return(0);
}