f11jpf solves a system of complex linear equations involving the incomplete Cholesky preconditioning matrix generated by
f11jnf.
f11jpf solves a system of linear equations
involving the preconditioning matrix
, corresponding to an incomplete Cholesky decomposition of a complex sparse Hermitian matrix stored in symmetric coordinate storage (SCS) format (see
Section 2.1.2 in the
F11 Chapter Introduction), as generated by
f11jnf.
In the above decomposition
is a complex lower triangular sparse matrix with unit diagonal,
is a real diagonal matrix and
is a permutation matrix.
and
are supplied to
f11jpf through the matrix
which is a lower triangular
complex sparse matrix, stored in SCS format, as returned by
f11jnf. The permutation matrix
is returned from
f11jnf via the array
ipiv.
f11jpf may also be used in combination with
f11jnf to solve a sparse complex Hermitian positive definite system of linear equations directly (see
f11jnf).
None.
If on entry
or
, explanatory error messages are output on the current error message unit (as defined by
x04aaf).
-
On entry, is out of order: .
On entry, , and .
Constraint: and .
On entry, , , .
Constraint: and .
On entry, , and .
Constraint: and .
On entry, is a repeated value: .
On entry,
istr appears to be invalid.
On entry,
is inconsistent with
irow:
.
On entry, the location () is a duplicate: .
Check that
a,
irow,
icol,
ipiv and
istr have not been corrupted between calls to
f11jnf and
f11jpf.
The computed solution
is the exact solution of a perturbed system of equations
, where
is a modest linear function of
, and
is the
machine precision.
Background information to multithreading can be found in the
Multithreading documentation.
The time taken for a call to
f11jpf is proportional to the value of
nnzc returned from
f11jnf.
This example reads in a complex sparse Hermitian positive definite matrix
and a vector
. It then calls
f11jnf, with
and
, to compute the
complete Cholesky decomposition of
:
Finally it calls
f11jpf to solve the system