NAG AD Library Routine Document

e04dg_a1w_f (uncon_conjgrd_comp_a1w)


Note: _a1w_ denotes that first order adjoints are computed in working precision; this has the corresponding argument type nagad_a1w_w_rtype. Further implementations, for example for higher order differentiation or using the tangent linear approach, may become available at later marks of the NAG AD Library. The method of codifying AD implementations in routine name and corresponding argument types is described in the NAG AD Library Introduction.

1
Purpose

e04dg_a1w_f is the adjoint version of the primal routine e04dgf .

2
Specification

Fortran Interface
Subroutine e04dg_a1w_f (ad_handle, n, objfun, iter, objf, objgrd, x, iwork, work, iuser, ruser, lwsav, iwsav, rwsav, ifail)
Integer, Intent (In):: n
Integer, Intent (Inout):: iuser(*), iwsav(610), ifail
Integer, Intent (Out):: iter, iwork(n+1)
Type (nagad_a1w_w_rtype), Intent (Inout):: x(n), ruser(*), rwsav(475)
Type (nagad_a1w_w_rtype), Intent (Out):: objf, objgrd(n), work(13*n)
Logical, Intent (Inout):: lwsav(120)
Type (c_ptr), Intent (In):: ad_handle
External:: objfun
Subroutine objfun (ad_handle, mode, n, x, objf, objgrd, nstate, iuser, ruser)
Integer, Intent (In):: n, nstate
Integer, Intent (Inout):: mode, iuser(*)
Type (nagad_a1w_w_rtype), Intent (Inout):: x(n), ruser(*), objf, objgrd(n)
Type (c_ptr), Intent (In):: ad_handle
C++ Header Interface
#include <nagad.h>
void e04dg_a1w_f_ (void *&ad_handle, const Integer &n,
void (NAG_CALL objfun)(void *&ad_handle, Integer &mode, const Integer &n, nagad_a1w_w_rtype x[], nagad_a1w_w_rtype &objf, nagad_a1w_w_rtype objgrd[], const Integer &nstate, Integer iuser[], nagad_a1w_w_rtype ruser[]),
Integer &iter, nagad_a1w_w_rtype &objf, nagad_a1w_w_rtype objgrd[], nagad_a1w_w_rtype x[], Integer iwork[], nagad_a1w_w_rtype work[], Integer iuser[], nagad_a1w_w_rtype ruser[], logical lwsav[], Integer iwsav[], nagad_a1w_w_rtype rwsav[], Integer &ifail)

3
Description

e04dgf minimizes an unconstrained nonlinear function of several variables using a pre-conditioned, limited memory quasi-Newton conjugate gradient method. First derivatives (or an ‘acceptable’ finite difference approximation to them) are required. It is intended for use on large scale problems. For further information see Section 3 in the documentation for e04dgf .

4
References

None.

5
Arguments

e04dg_a1w_f provides access to all the arguments available in the primal routine. There are also additional arguments specific to AD. A tooltip popup for each argument can be found by hovering over the argument name in Section 2 and a summary of the arguments are provided below:

6
Error Indicators and Warnings

e04dg_a1w_f preserves all error codes from e04dgf and in addition can return:
ifail=-89
An unexpected AD error has been triggered by this routine. Please contact NAG.
See Section 5.2 in the NAG AD Library Introduction for further information.
ifail=-899
Dynamic memory allocation failed for AD.
See Section 5.1 in the NAG AD Library Introduction for further information.

7
Accuracy

Not applicable.

8
Parallelism and Performance

e04dg_a1w_f is not threaded in any implementation.

9
Further Comments

None.

10
Example

The following examples are variants of the example for e04dgf , modified to demonstrate calling the NAG AD Library.
LanguageSource FileDataResults
Fortane04dg_a1w_fe.f90e04dg_a1w_fe.de04dg_a1w_fe.r
C++e04dg_a1w_hcppe.cppe04dg_a1w_hcppe.de04dg_a1w_hcppe.r