cg cg1 cg_r cr cr_r

cg1() void cg1 ( char  uplo, int  n, const double  val[], const int  rowptr[], const int  colind[], const double  b[], double  x[], double  tol, int  maxiter, int *  iter, double *  res, int  lwork, double  work[], int *  info  ) Solution of linear system Ax = b using conjugate gradient (CG) method (Symmetric positive definite) (Simple driver) Purpose This routine solves the linear system Ax = b with symmetric positive definite coefficient matrix using the conjugate gradient (CG) method. Matrix A is represented in CSR format. Parameters [in] uplo Specifies whether the upper or lower triangular part of matrix A is stored. = 'U': Upper triangular part is stored. = 'L': Lower triangular part is stored. = 'F': Full matrix (both upper and lower triangular parts) are stored. [in] n Dimension of the matrix. (n >= 0) (If n = 0, returns without computation) [in] val[] Array val[lval] (lval >= nnz) Values of nonzero elements of matrix A (where nnz is the number of nonzero elements). [in] rowptr[] Array rowptr[lrowptr] (lrowptr >= n + 1) Row pointers of matrix A. [in] colind[] Array colind[lcolind] (lcolind >= nnz) Column indices of matrix A (where nnz is the number of nonzero elements). [in] b[] Array b[lb] (lb >= n) Right hand side vector b. [in,out] x[] Array x[lx] (lx >= n) [in] Initial guess of solution. [out] Obtained approximate solution. [in] tol Tolerance for convergence test. Assumed to be converged if norm(b - A*x) <= tol*norm(b). If tol < eps (machine epsilon), tol = eps is assumed. [in] maxiter Maximum number of iterations. (maxiter > 0) [out] iter Final number of iterations. [out] res Final residual norm norm(b - A*x). [in] lwork Size of array work[]. (lwork >= 5*n) [out] work[] Array work[lwork] Work array. [out] info = 0: Successful exit. < 0: The (-info)-th argument is invalid. = 1: (Warning) Matrix A is not positive definite (computation continued). = 2: (Warning) Preconditioner matrix M is not positive definite (computation continued). = 11: Maximum number of iterations exceeded. = 12: Matrix A is singular.