-*> \brief <b> CGESV computes the solution to system of linear equations A * X = B for GE matrices</b> (simple driver) </b>
+*> \brief <b> CGESV computes the solution to system of linear equations A * X = B for GE matrices (simple driver) </b>
*
* =========== DOCUMENTATION ===========
*
*> \par References:
* ================
*>
+*> \verbatim
+*>
*> [1] P. P. M. De Rijk: A one-sided Jacobi algorithm for computing the
*> singular value decomposition on a vector computer.
*> SIAM J. Sci. Stat. Comp., Vol. 10 (1998), pp. 359-371.
*> positive definite.
*> This routine use the 2stage technique for the reduction to tridiagonal
*> which showed higher performance on recent architecture and for large
-* sizes N>2000.
+*> sizes N>2000.
*> \endverbatim
*
* Arguments:
*> \verbatim
*> LWORK is INTEGER
*> The dimension of the array WORK which should be calculated
-* by a workspace query. LWORK = MAX(1, LWORK_QUERY)
+*> by a workspace query. LWORK = MAX(1, LWORK_QUERY)
*> If LWORK = -1, then a workspace query is assumed; the routine
*> only calculates the optimal size of the WORK array, returns
*> this value as the first entry of the WORK array, and no error
*>
*> where tau is a complex scalar, and v is a complex vector with
*> v(kd+1:i) = 0 and v(i+kd+1) = 1; v(i+kd+2:n) is stored on exit in
-* A(i+kd+2:n,i), and tau in TAU(i).
+*> A(i+kd+2:n,i), and tau in TAU(i).
*>
*> The contents of A on exit are illustrated by the following examples
*> with n = 5:
*
*
*> \par Purpose:
-*> =============
+* =============
*>
*>\verbatim
*>
*
*
*> \par Purpose:
-*> =============
+* =============
*>
*>\verbatim
*>
*
*
*> \par Purpose:
-*> =============
+* =============
*>
*>\verbatim
*>
*
*
*> \par Purpose:
-*> =============
+* =============
*>
*>\verbatim
*>
*
*
*> \par Purpose:
-*> =============
+* =============
*>
*>\verbatim
*>
*
*
*> \par Purpose:
-*> =============
+* =============
*>
*>\verbatim
*>
*
*
*> \par Purpose:
-*> =============
+* =============
*>
*>\verbatim
*>
*
*
*> \par Purpose:
-*> =============
+* =============
*>
*>\verbatim
*>
*
*
*> \par Purpose:
-*> =============
+* =============
*>
*>\verbatim
*>
*
*
*> \par Purpose:
-*> =============
+* =============
*>
*>\verbatim
*>
*
*
*> \par Purpose:
-*> =============
+* =============
*>
*>\verbatim
*>
*
*
*> \par Purpose:
-*> =============
+* =============
*>
*>\verbatim
*>
*
*
*> \par Purpose:
-*> =============
+* =============
*>
*>\verbatim
*>
*
*
*> \par Purpose:
-*> =============
+* =============
*>
*>\verbatim
*>
*> positive definite.
*> This routine use the 2stage technique for the reduction to tridiagonal
*> which showed higher performance on recent architecture and for large
-* sizes N>2000.
+*> sizes N>2000.
*> \endverbatim
*
* Arguments:
*> \verbatim
*> LWORK is INTEGER
*> The dimension of the array WORK which should be calculated
-* by a workspace query. LWORK = MAX(1, LWORK_QUERY)
+*> by a workspace query. LWORK = MAX(1, LWORK_QUERY)
*> If LWORK = -1, then a workspace query is assumed; the routine
*> only calculates the optimal size of the WORK array, returns
*> this value as the first entry of the WORK array, and no error
*>
*> where tau is a real scalar, and v is a real vector with
*> v(kd+1:i) = 0 and v(i+kd+1) = 1; v(i+kd+2:n) is stored on exit in
-* A(i+kd+2:n,i), and tau in TAU(i).
+*> A(i+kd+2:n,i), and tau in TAU(i).
*>
*> The contents of A on exit are illustrated by the following examples
*> with n = 5:
*>
*> [ A11 | A12 ] where A11 is n1 by n1 and A22 is n2 by n2
*> A = [ -----|----- ] with n1 = min(m,n)/2
-* [ A21 | A22 ] n2 = n-n1
+*> [ A21 | A22 ] n2 = n-n1
*>
*> [ A11 ]
*> The subroutine calls itself to factor [ --- ],
*
*
*> \par Purpose:
-*> =============
+* =============
*>
*>\verbatim
*>
*
*
*> \par Purpose:
-*> =============
+* =============
*>
*>\verbatim
*>
*
*
*> \par Purpose:
-*> =============
+* =============
*>
*>\verbatim
*>
*
*
*> \par Purpose:
-*> =============
+* =============
*>
*>\verbatim
*>
*
*
*> \par Purpose:
-*> =============
+* =============
*>
*>\verbatim
*>
*
*
*> \par Purpose:
-*> =============
+* =============
*>
*>\verbatim
*>
*
*
*> \par Purpose:
-*> =============
+* =============
*>
*>\verbatim
*>
*> positive definite.
*> This routine use the 2stage technique for the reduction to tridiagonal
*> which showed higher performance on recent architecture and for large
-* sizes N>2000.
+*> sizes N>2000.
*> \endverbatim
*
* Arguments:
*> \verbatim
*> LWORK is INTEGER
*> The dimension of the array WORK which should be calculated
-* by a workspace query. LWORK = MAX(1, LWORK_QUERY)
+*> by a workspace query. LWORK = MAX(1, LWORK_QUERY)
*> If LWORK = -1, then a workspace query is assumed; the routine
*> only calculates the optimal size of the WORK array, returns
*> this value as the first entry of the WORK array, and no error
*>
*> where tau is a real scalar, and v is a real vector with
*> v(kd+1:i) = 0 and v(i+kd+1) = 1; v(i+kd+2:n) is stored on exit in
-* A(i+kd+2:n,i), and tau in TAU(i).
+*> A(i+kd+2:n,i), and tau in TAU(i).
*>
*> The contents of A on exit are illustrated by the following examples
*> with n = 5:
-*> \brief <b> ZGESV computes the solution to system of linear equations A * X = B for GE matrices</b> (simple driver) </b>
+*> \brief <b> ZGESV computes the solution to system of linear equations A * X = B for GE matrices (simple driver) </b>
*
* =========== DOCUMENTATION ===========
*
*> \par References:
* ================
*>
+*> \verbatim
+*>
*> [1] P. P. M. De Rijk: A one-sided Jacobi algorithm for computing the
*> singular value decomposition on a vector computer.
*> SIAM J. Sci. Stat. Comp., Vol. 10 (1998), pp. 359-371.
*> positive definite.
*> This routine use the 2stage technique for the reduction to tridiagonal
*> which showed higher performance on recent architecture and for large
-* sizes N>2000.
+*> sizes N>2000.
*> \endverbatim
*
* Arguments:
*> \verbatim
*> LWORK is INTEGER
*> The dimension of the array WORK which should be calculated
-* by a workspace query. LWORK = MAX(1, LWORK_QUERY)
+*> by a workspace query. LWORK = MAX(1, LWORK_QUERY)
*> If LWORK = -1, then a workspace query is assumed; the routine
*> only calculates the optimal size of the WORK array, returns
*> this value as the first entry of the WORK array, and no error
*>
*> where tau is a complex scalar, and v is a complex vector with
*> v(kd+1:i) = 0 and v(i+kd+1) = 1; v(i+kd+2:n) is stored on exit in
-* A(i+kd+2:n,i), and tau in TAU(i).
+*> A(i+kd+2:n,i), and tau in TAU(i).
*>
*> The contents of A on exit are illustrated by the following examples
*> with n = 5:
*
*
*> \par Purpose:
-*> =============
+* =============
*>
*>\verbatim
*>
*
*
*> \par Purpose:
-*> =============
+* =============
*>
*>\verbatim
*>
*
*
*> \par Purpose:
-*> =============
+* =============
*>
*>\verbatim
*>
*
*
*> \par Purpose:
-*> =============
+* =============
*>
*>\verbatim
*>
*
*
*> \par Purpose:
-*> =============
+* =============
*>
*>\verbatim
*>
*
*
*> \par Purpose:
-*> =============
+* =============
*>
*>\verbatim
*>
*
*
*> \par Purpose:
-*> =============
+* =============
*>
*>\verbatim
*>